SURFACE SIMULATION
FIELD OF THE INVENTION
The invention relates to surface simulation.
BACKGROUND
The present invention, in some embodiments thereof, relates to IR (Infra Red)
images and radiometric data, and, more particularly, but not exclusively, to creation by
calculation i.e. by modeling and analysis of IR images , IR data and radiometric data.
The use of imaging in diagnostic medicine dates back to the early 1900s.
Presently there are numerous different imaging modalities at the disposal of a
physician allowing imaging of hard and soft tissues and characterization of both
normal and pathological tissues.
Infrared cameras produce two-dimensional images known as IR (Infra Red)
images. IR image is typically obtained by receiving from the body of the subject
radiation at any one of several infrared wavelength ranges and analyzing the radiation
to provide a two-dimensional radiometric map of the surface (i.e. temperature). The IR
image can be in the form of either or both of a visual image and corresponding
radiometric data.
U.S. Patent No. 7,072,504 the contents of which are hereby incorporated by
reference, discloses an approach which utilizes two infrared cameras (left and right) in
combination with two visible light cameras (left and right). The infrared cameras are
used to provide a three-dimensional thermographic image and the visible light cameras
are used to provide a three-dimensional visible light image. The three-dimensional
thermographic and three-dimensional visible light images are displayed to the user in
an overlapping manner.
U.S. Patent No. 7,292,719, the contents of which are hereby incorporated by
reference discloses a system for determining presence or absence of one or more
thermally distinguishable objects in a living body.
Also of interest is U.S. Patent No. 6,442,419 discloses a scanning system
including an infrared detecting mechanism which performs a 360° data extraction from
an object, and a signal decoding mechanism, which receives electrical signal from the
infrared detecting mechanism and integrates the signal into data of a three-dimensional
profile of the object.
U.S. Patent No. 6,850,862 discloses an apparatus which uses radiometric
sensors to detect radiation from various layers within the object over a range of
wavelengths from radio waves through the infrared.
U.S. Patent No. 5,961,466 discloses detection of breast cancer from a rapid time
series of infrared images which is analyzed to detect changes in the distribution of
thermoregulatory frequencies over different areas of the skin.
SUMMARY
The following embodiments and aspects thereof are described and illustrated in
conjunction with systems, tools and methods which are meant to be exemplary and
illustrative, not limiting in scope.
There is provided, in accordance with an embodiment, an imaging method
comprising: receiving a spatial infra-red (IR) representation of a curved body section,
wherein the spatial IR representation comprises a IR image associated with spatial
data; and generating a calculated thermal simulation of the curved body section,
wherein said generating of the theoretical thermal simulation is based on the spatial
data of the representation and on predetermined thermodynamic logic of a type of the
curved body section.
There is further provided, in accordance with an embodiment, an imaging system
comprising: an imaging device; and a hardware data processor configured to: (a)
generate a spatial thermal representation of a curved body section, wherein the spatial
thermal representation comprises a thermal image associated with spatial data, and (b)
generate a theoretical thermal simulation of the curved body section, wherein said
generate of the theoretical thermal simulation is based on the spatial data of the
representation and on predetermined thermodynamic logic of a type of the curved body
section.
There is yet further provided, in accordance with an embodiment, an imaging
method comprising: receiving spatial data of a curved body section; and generating a
theoretical thermal simulation of the curved body section, wherein said generating of
the theoretical thermal simulation is based on the spatial data of the representation and
on predetermined thermodynamic logic of a type of the curved body section.
In some embodiments, the method further comprises receiving a spatial thermal
representation of the curved body section, wherein the spatial thermal representation
comprises said spatial data and a thermal image associated with said spatial data.
In some embodiments, the method further comprises comparing the spatial
thermal representation and the theoretical thermal simulation.
In some embodiments, the method further comprises detecting an abnormality in
the curved body section, wherein said detecting is based on said comparing of the
spatial thermal representation and the theoretical thermal simulation.
In some embodiments, the method further comprises back-solving a parameter of
the abnormality inside the curved body section.
In some embodiments, said back-solving comprises: generating a plurality of
additional theoretical thermal simulations of a theoretical tumor inside the curved body
section, wherein, in each simulation of the plurality of additional theoretical thermal
simulations, a parameter of the theoretical tumor is adjusted; and comparing the spatial
thermal representation and the plurality of additional theoretical thermal simulations,
to determine which simulation of the plurality of additional theoretical thermal
simulations is closest to the representation.
In some embodiments, the parameter of the abnormality is selected from the
group consisting of: a location of the abnormality inside the curved body section, a
size of the abnormality and a shape of the abnormality.
In some embodiments, said spatial thermal representation is responsive to a cold
stress test, thereby enhancing a contrast between the abnormality and a normal tissue
adjacent to the abnormality.
In some embodiments, the predetermined thermodynamic logic is under an
influence of a theoretical cold stress test.
In some embodiments, the predetermined thermodynamic logic of the type of the
curved body section is computed based on healthy subjects.
In some embodiments, the curved body section comprises one or more breasts.
In some embodiments, said hardware data processor is further configured to
compare the spatial thermal representation and the theoretical spatial thermal
simulation.
In some embodiments, said hardware data processor is further configured to
detect an abnormality in the curved body section, wherein said detect is based on said
comparing of the spatial thermal representation and the theoretical thermal simulation.
In some embodiments, said hardware data processor is further configured to
back-solve a parameter of the abnormality inside the curved body section.
In some embodiments, said back-solve comprises: generating a plurality of
additional theoretical thermal simulations of a theoretical tumor inside the curved body
section, wherein, in each simulation of the plurality of additional theoretical thermal
simulations, a parameter of the theoretical tumor is adjusted; and comparing the spatial
thermal representation and the plurality of additional theoretical thermal simulations,
to determine which simulation of the plurality of additional theoretical thermal
simulations is closest to the representation.
In some embodiments, said imaging device comprises a thermal imaging device
and a visible light imaging device.
In addition to the exemplary aspects and embodiments described above, further
aspects and embodiments will become apparent by reference to the figures and by
study of the following detailed description.
BRIEF DESCRIPTION OF THE FIGURES
Exemplary embodiments are illustrated in referenced figures. Dimensions of
components and features shown in the figures are generally chosen for convenience
and clarity of presentation and are not necessarily shown to scale. The figures are
listed below.
Fig. 1A shows a three-dimensional spatial representation illustrated as a nonplanar
surface, in accordance with an embodiment;
Fig. IB shows a thermographic image illustrated as planar isothermal contours,
in accordance with an embodiment;
Fig. 1C shows a synthesized IR-spatial image formed by mapping the
thermographic image on a surface of the three-dimensional spatial representation, in
accordance with an embodiment;
Fig. 2 shows a flow chart of a method suitable for analyzing a thermal image of a
body section, in accordance with an embodiment;
Fig. 3 shows a flowchart of another method suitable for analyzing a thermal
image of a body section, in accordance with an embodiment;
Fig. 4 shows a flowchart of another method suitable for analyzing a thermal
image of a body section, in accordance with an embodiment;
Fig. 5 shows a flowchart of another method suitable for analyzing a thermal
image of a body section, in accordance with an embodiment;
Fig. 6A shows a schematic illustration of an IR-spatial imaging system, in
accordance with an embodiment;
Fig. 6B shows an illustration of an operation principle of IR-spatial imaging
system, in accordance with an embodiment;
Fig. 6C shows an illustration of another operation principle of IR-spatial imaging
system, in accordance with an embodiment;
Fig. 7A shows an illustration of another operation principle of IR-spatial imaging
system, in accordance with an embodiment;
Fig. 7B shows an illustration of another operation principle of IR-spatial imaging
system, in accordance with an embodiment;
Fig. 7C shows an illustration of another operation principle of IR-spatial imaging
system, in accordance with an embodiment;
Fig. 7D shows an illustration of another operation principle of IR-spatial imaging
system, in accordance with an embodiment;
Fig. 7E shows an illustration of another operation principle of IR-spatial imaging
system, in accordance with an embodiment;
Fig. 8A shows a pictorial view of a spatial thermal representation of breasts of a
healthy subject;
Fig. 8B shows a pictorial view of a theoretical thermal simulation of the breasts
of the healthy subject;
Fig. 8C shows a pictorial view of a comparison between the spatial thermal
representation of the breasts of the healthy subject and the theoretical thermal
simulation of the breasts of the healthy subject;
Fig. 9A shows a pictorial view of a spatial thermal representation of breasts of an
unhealthy subject;
Fig. 9B shows a pictorial view of a theoretical thermal simulation of the breasts
of the unhealthy subject; and
Fig. 9C shows a pictorial view of a comparison between the spatial thermal
representation of the breasts of the unhealthy subject and the theoretical thermal
simulation of the breasts of the unhealthy subject.
DETAILED DESCRIPTION
An imaging method for generating a thermal simulation of a curved body section
is disclosed herein. The present invention, in some embodiments thereof, relates to
thermal images and, more particularly, but not exclusively, to the creation and analysis
of IR images and thermal data.
Before explaining at least one embodiment of the invention in detail, it is to be
understood that the invention is not necessarily limited in its application to the details
of construction and the arrangement of the components and/or methods set forth in the
following description and/or illustrated in the drawings and/or the Examples. The
invention is capable of other embodiments or of being practiced or carried out in
various ways.
In accordance with some embodiments, an imaging method may include
generating, or receiving an already-generated spatial thermal representation of a curved
body section, such as one or more female breasts. This spatial thermal representation
includes a thermal (e.g. IR) image associated with spatial data of the curved body
section. Then, a theoretical thermal simulation of the curved body section is generated,
based on the spatial data of the representation and on predetermined thermodynamic
logic of a type of the curved body section. The thermodynamic logic of a type of the
curved body section may be, for example, the general thermodynamic behavior of a
female's breasts. Advantageously, the thermodynamic logic is based on mathematical
modeling of a general case of female breasts, constructed based on the thermodynamic
behavior of breasts of healthy subjects.
In some embodiments, the spatial thermal representation and the theoretical
thermal simulation are compared. Each of the spatial thermal representation and the
theoretical thermal simulation may be constructed as a three-dimensional heat map,
showing the temperature at different regions of the curved body section. Accordingly,
their comparison may include deducting the theoretical thermal simulation from the
spatial thermal representation, thereby obtaining a three-dimensional heat map of the
thermal difference between the thermal behavior exhibited in reality by the curved
body section and the theoretical thermal behavior of a healthy curved body section.
The difference may be indicative of an abnormality in the curved body section, such
as, for example, the existence of one or more tumors in the breast. The term "tumor",
as referred to herein, may relate to an abnormal mass of tissue, whether malignant, premalignant
or benign.
In some embodiments, the method further includes back-solving a parameter of
the abnormality inside the curved body section. The term "back solving", as referred to
herein, may relate to the computing method also known as "goal seeking", which is
often defined as the ability to calculate backward to obtain an input that would result in
a given output. In the context of present embodiments, the output is the determination
that a tumor exists in one or more of the breasts, as well as the particular representation
of that tumor in the spatial thermal representation which was obtained. The purpose of
the back solving may be to determine or at least estimate the real (or nea -real) threedimensional
location, size, shape and/or density of the tumor inside the curved body
section, based on its manifestation in the spatial thermal representation. Namely, the
input sought by the back solving process is the actual location of the tumor inside the
breast, whereas the output available is the manifestation of the tumor in the spatial
thermal representation. The back solving may be further aimed at assessing the type of
the abnormality, namely to categorize it as a benign or malignant tumor, and
optionally, if the tumor is malignant, to determine its stage.
The back solving may be conducted as follows: first, the present method
generates a plurality of additional theoretical thermal simulations of a theoretical
tumor inside the curved body section. In other words, the method generates many (for
example dozens, hundreds, thousands or more) possible inputs, each being of a
theoretical abnormality (tumor) structured and positioned differently inside the curved
body section. That is, a parameter of the abnormality is adjusted for each subsequent
generation of an input. The parameters may be, for example, the location of the
abnormality inside the curved body section, its shape and/or size.
Then, the method may compare the spatial thermal representation and the
plurality of inputs (namely, the additional theoretical thermal simulations), to
determine which input is the closest one to the representation. For example, it may be
determined that a tumor characterized by a shape and a size A and located at
coordinates B is the likely cause of the abnormality visualized in the spatial thermal
representation.
In some embodiments, the subject may be subjected to a cold stress test prior to
and/or during the acquisition of the thermal image and the spatial data. The cold stress
test may include, for example, instructing the subject to hold a cold object, such as a
container filled with a frozen liquid, in one or both hands. Accordingly, the resulting
spatial thermal representation is responsive to the subject's body reaction to the cold
stress test. The cold stress test may enhance the contrast between the abnormality and a
normal tissue adjacent to the abnormality, since the cold may not influence the blood
flow to the abnormality at a higher level than the decrease of blood flow to normal
tissue adjacent to the abnormality.
In some embodiments, the method or at least parts thereof may be carried out by
an imaging system which includes an imaging device and a hardware data processor.
The processor may be configured to, for example (a) generate the spatial thermal
representation and (b) generate the theoretical thermal simulation of the curved body
section.
Embodiments of the present invention provide an approach which may enable
the analysis of a thermal image, e.g., for the purpose of determining the likelihood that
the image indicates presence of a thermally distinguishable region. When the thermal
image is of a body section such as a breast of a woman, the analysis of the present
embodiments may be advantageously used to extract properties of the underlying
tissue. For example, determination of the likelihood that a thermally distinguished
region is present in the body section may be used to for assessing whether or not the
body section may have pathology such as a tumor.
The analysis according to some embodiments of the present invention may be
based on surface information obtained from the surface of the body section. Generally,
the measured surface information may be compared to a predicted or may calculate
surface information. In some embodiments of the present invention the surface
comparison may relate to the likelihood that a thermally distinguishable region, e.g., a
tumor or an inflammation, is present in the body section.
An elevated temperature or non-uniform temperature or a non-uniform
temperature pattern may be generally associated with a tumor due to the metabolic
abnormality of the tumor and proliferation of blood vessels (angiogenesis) at and/or
near the tumor and on the breast surface. In a cancerous tumor the cells may double
faster and thus may be more active and generate more heat. This tends to enhance the
temperature differential between the tumor itself and the surrounding temperature. The
present embodiments may therefore be advantageously used for diagnosis of cancer,
particularly, but not exclusively breast cancer.
The surface information used for the analysis may comprise spatial information
as well as optionally thermal information.
The spatial information may comprise data pertaining to geometric properties of
a non-planar (i.e. curved) surface which may at least partially enclose a threedimensional
volume. Generally, the non-planar surface may be a two-dimensional
object embedded in a three-dimensional space. Formally, a non-planar surface may be a
metric space induced by a smooth connected and compact Riemannian 2-manifold.
Ideally, the geometric properties of the non-planar surface would be provided
explicitly, for example, the slope and curvature (or even other spatial derivatives or
combinations thereof) for every point of the non-planar surface. Yet, such information
may be rarely attainable and the spatial information may be provided for a sampled
version of the non-planar surface, which may be a set of points on the Riemannian 2-
manifold and which may be sufficient for describing the topology of the 2-manifold.
Typically, the spatial information of the non-planar surface may be a reduced version
of a three-dimensional spatial representation, which may be either a point-cloud or a
three-dimensional reconstruction (e.g., a polygonal mesh or a curvilinear mesh) based
on the point cloud. The three-dimensional spatial representation may be expressed via a
three-dimensional coordinate system, such as, but not limited to, Cartesian, Spherical,
Ellipsoidal, three-dimensional Parabolic or Paraboloidal coordinate three-dimensional
system.
The term "surface" is used herein as an abbreviation of the term "non-planar
surface".
The spatial data, in some embodiments of the present invention, may be in a
form of an image. Since the spatial data may represent the surface, such image is
typically a two-dimensional image which, in addition to indicating the lateral extent of
body members, may further indicate the relative or absolute distance of the body
members, or portions thereof, from some reference point, such as the location of the
imaging device. Thus, the image may typically include information residing on a nonplanar
surface of a three-dimensional body and not necessarily in the bulk. Yet, it is
commonly acceptable to refer to such image as "a three-dimensional image" because
the non-planar surface is conveniently defined over a three-dimensional system of
coordinate. Thus, throughout this specification and in the claims section that follows,
the terms "three-dimensional image" and "three-dimensional representation" primarily
relate to surface entities.
The thermal information may comprise data pertaining to heat evacuated from
or absorbed by the surface and/or to an IR (Infra Red) radiation emitted from the
surface. Since different parts of the surface may generally evacuate or absorb different
amount of heat, the thermal information may comprise a set of tuples, each may
comprise the coordinates of a region or a point on the surface and a thermal numerical
value (e.g., temperature, thermal energy) associated with the point or region. The
thermal information may be transformed to visible signals, in which case the thermal
information may be in the form of a thermographic image. The terms "thermographic
image", "IR image", "thermal image" and "thermal information" are used
interchangeably throughout the specification without limiting the scope of the present
invention in any way. Specifically, unless otherwise defined, the use of the term
"thermographic image" is not to be considered as limited to the transformation of the
thermal information into visible signals. For example, a thermographic image may be
stored in the memory of a computer readable medium as a set of tuples as described
above.
The surface information (thermal and spatial) of a body may be typically in the
form of a synthesized representation which may include both IR data representing the
IR image and spatial data representing the surface, where the IR data may be associated
with the spatial data (i.e., a tuple of the spatial data is associated with a heat-related
value of the IR data). Such representation may be referred to as an IR-spatial
representation. The IR-spatial representation may be in the form of digital data (e.g., a
list of tuples associated with digital data describing thermal quantities) or in the form of
an image (e.g., a three-dimensional image color-coded or grey-level coded according to
the IR data). An IR-spatial representation in the form of an image is referred to
hereinafter as an IR-spatial image.
The IR-spatial image may be defined over a three-dimensional spatial
representation of the body and has thermal data associated with a surface of the threedimensional
spatial representation, and arranged gridwise over the surface in a plurality
of picture-elements (e.g., pixels, arrangements of pixels), each represented by an
intensity value or a grey-level over the grid. It is appreciated that the number of
different intensity value may be different from the number of grey-levels. For example,
an 8-bit display may generate 256 different grey-levels. However, in principle, the
number of different intensity values corresponding to thermal information may be
much larger. As a representative example, suppose that the thermal information spans
over a range of 37 °C and may be digitized with a resolution of 0.1 °C. In this case,
there may be 370 different intensity values and the use of grey-levels may be less
accurate by a factor of approximately 1.4. In some embodiments of the present
invention the processing of thermal data may be performed using intensity values,
temperature values, and in some embodiments of the present invention the processing
of thermal data may be performed using grey-levels. Combinations of the two (such as
double processing) may be also contemplated.
The term "pixel" is sometimes abbreviated herein to indicate a picture-element.
However, this is not intended to limit the meaning of the term "picture-element" which
refers to a unit of the composition of an image.
When the IR-spatial representation may be in the form of digital data, the digital
data describing thermal properties may also be expressed either in terms of intensities
or in terms of grey-levels as described above. Digital IR-spatial representation may also
correspond to IR-spatial image whereby each tuple corresponds to a picture-element of
the image.
Typically, one or more IR images, either measured or calculated, may be
mapped onto the surface of the three-dimensional spatial representation to form the IRspatial
representation. The IR image to be mapped onto the surface of the threedimensional
spatial representation may comprise thermal data and/or IR data which
may be expressed over the same coordinate system as the three-dimensional spatial
representation. Any type of thermal data may be used. In one embodiment the thermal
data may comprise absolute temperature values. In another embodiment the thermal
data may comprise relative temperature values, each corresponding to, e.g., a
temperature difference between a respective point of the surface and some reference
point. In an additional embodiment, the thermal data may comprise local temperature
differences. Also contemplated, are combinations of the above types of temperature
data, for example, the thermal data may comprise both absolute and relative
temperature values, and the like.
Typically, but not obligatorily, the information in the thermographic image may
also include the thermal conditions (e.g., temperature) at one or more reference
markers.
The mapping of the thermographic image onto the surface of the threedimensional
spatial representation may be done by positioning the reference markers,
(e.g., by comparing their coordinates in the IR image with their coordinates in the
three-dimensional spatial representation), to thereby match also other points hence to
form the synthesized IR-spatial representation.
Optionally , the mapping of IR images may be accompanied by a correction
procedure in which thermal emissivity considerations may be employed.
The thermal emissivity of a body member is a dimensionless quantity defined as
the ratio between the amount of IR radiation emitted from the surface of the body
member and the amount of IR radiation emitted from a black body having the same
temperature as the body member. Thus, the thermal emissivity of an idealized black
body is 1 and the thermal emissivity of all other bodies is between 0 and 1. It is
commonly assumed that the thermal emissivity of a body is generally equal to its
thermal absorption factor.
The correction procedure may be performed using estimated thermal
characteristics of the body of interest. Specifically, the IR image may be mapped onto a
non-planar surface describing the body taking into account differences in the emissivity
of regions on the surface of the body and the emissivity's angular dependence. A region
with a different emissivity value compared to its surroundings may be, for example, a
scarred region, a pigmented region, a nipple region on the breast, a nevus, etc. In
addition, assuming that the human skin is not perfect Lambertian source, the emissivity
is angle dependent. Another consideration should take into account the possibility that
the emissivity values of subjects with different skin colors may differ.
In some embodiments of the present invention, the IR image may be weighted
according to the different emissivity values of the surface. For example, when
information acquired by an IR imaging device include temperature or energy values, at
least a portion of the temperature or energy values may be divided by the emissivity
values of the respective regions on the surface of the body. One of ordinary skill in the
art may appreciate that such procedure results in effective temperature or energy values
which might be different than the values acquired by the IR imaging device. Since
different regions may be characterized by different emissivity values, the weighted IR
image may provide better estimation regarding the heat emitted from the surface of the
body.
A representative example of a synthesized IR-spatial image for the case that the
body comprise the breasts of a woman is illustrated in Figures 1A-C, which show a
three-dimensional spatial representation illustrated as a non-planar surface (Figure 1A),
a thermographic image illustrated as planar isothermal contours (Figure IB), and a
synthesized IR-spatial image formed by mapping the thermographic image on a surface
of the three-dimensional spatial representation (Figure 1C). As illustrated, the IR data
of the IR-spatial image may be represented as grey-level values optionally but not
necessarily over a grid generally shown at 102. It is to be understood that the
representation according to grey-level values is for illustrative purposes and is not to be
considered as limiting. As explained above, the processing of thermal data may also be
performed using intensity values. Also shown in Figures 1A-C, is a reference marker
101 which optionally, but not obligatorily, may be used for the mapping.
The three-dimensional spatial representation, thermographic image and
synthesized IR-spatial image may be obtained in any technique known in the art, such
as the technique disclosed in International Patent Publication No. WO 2006/003658,
U.S. Published Application No. 20010046316, and U.S. Patent Nos. 6,442,419,
6,765,607, 6,965,690, 6,701,081, 6,801,257, 6,201,541, 6,167,151, 6,167,151,
6,094,198 and 7,292,719.
Some embodiments of the invention may be embodied on a tangible medium
such as a computer (or "hardware data processor") for performing the method steps.
Some embodiments of the invention may be embodied on a computer readable
medium, comprising computer readable instructions for carrying out the method steps.
Some embodiments of the invention may also be embodied in electronic device having
digital computer capabilities arranged to run the computer program on the tangible
medium or execute the instruction on a computer readable medium. Computer
programs implementing method steps of the present embodiments may commonly be
distributed to users on a tangible distribution medium. From the distribution medium,
the computer programs may be copied to a hard disk or a similar intermediate storage
medium. The computer programs may be run by loading the computer instructions
either from their distribution medium or their intermediate storage medium into the
execution memory of the computer, configuring the computer to act in accordance with
the method of this invention. All of these operations are well-known to those skilled in
the art of computer systems.
Figure 2 shows a flow chart of a method suitable for analyzing a thermal image
of a body section, according to some embodiments of the present invention. It is to be
understood that several method steps appearing in the following description or in the
flowchart diagram of Figure 2 are optional and may not be executed.
The method may begin at step 20 and may continue to step 22 in which a spatial
thermal representation (also referred as an IR-spatial representation) of the curved body
section is obtained. The IR-spatial representation, as stated, may include IR data
representing the thermal image and spatial data representing a non-planar surface of the
curved body section, where the IR data may be associated with spatial data. The IRspatial
representation may be generated by the method or it may be generated by
another method or system from which the IR-spatial representation may be read by the
method.
Optionally, the method may continue to step 24 in which the data in the IRspatial
representation may be preprocessed. The preprocessing may be done for the
thermal data, the spatial data, or the both spatial and IR data.
Preprocessing of IR data may include, without limitation, powering (e.g.,
squaring), normalizing, enhancing, smoothing and the like. Preprocessing of spatial
data may include, without limitation, removal, replacement and interpolation of picture -
elements, using various processing operations such as, but not limited to,
morphological operations (e.g., erosion, dilation, opening, closing), resizing operations
(expanding, shrinking), padding operations, equalization operations (e.g., via
cumulative density equalization, histogram equalization) and edge detection (e.g.,
gradient edge detection).
The method may proceed to step 26 which may be the first step for calculating
the theoretical thermal simulation over the surface in an analytically method or in any
other known method. There may be two major ways for calculating the temperature of
external body surface; solving analytically the heat transfer equation with the proper
boundary conditions and numerically by finite-element calculations or by other
numerical calculations techniques. Analytical heat transfer equation solutions exist only
for plane surfaces or symmetrical bodies like sphere or cylinder. For nonsymmetrical
bodies the finite-element method should be applied. However, the finite-element
method is may be too complicated when working in real time or with large shapes with
variety shapes and boundary conditions. Thus, different approach may be adopted. In
the present approach the theoretical thermal simulation over the surface may be
calculated analytically based on known analytical heat transfer equation solutions (also
referred as predetermined thermodynamic logic) based on behavior of a normal healthy
body and the spatial data representing a non-planar surface of the curved body section.
The first step in the calculation may be to define a reference point or isothermal surface
in the body.
Once the reference isothermal surface in the body may be defined, the method
may continue to step 28 in which the adequate distance of each point on the body's
surface to the calculated reference isothermal surface may be determined. In general,
the adequate distance of each point on the body's surface to the calculated reference
isothermal surface may be simply the distance between the point on the body's surface
to the nearest point on the calculated reference isothermal surface. The adequate
distance may also be determined by any other function. It may also be improved based
on trial and error Finite Element software (e.g. ANSYS) calculations.
After the adequate distance of each point on the body's surface to the calculated
reference isothermal surface may be determined, the method may continue to step 30 in
which the theoretical thermal simulation and/or IR data over the surface may be
calculated. In general, but not limited to, the calculation of a body thermal map may be
based on predetermined thermodynamic logic, for example the Pennes's bio-heat
equation. The solution of the Pennes's bio-heat equation with the proper boundary
conditions may determine the temperature of each point in the body as a function of its
coordinates.
quation of the human's body in cylindrical
co
Wb - is the volumetric blood perfusion rate (kg/s m3)
Cb - is blood specific heat (J/kg °C)
Kt - is tissue thermal conductivity (W/m K)
Tart - is arterial blood temperature (°C)
r - Radius (m)
Solving this differential equation for certain boundary conditions may attain an
equation that may give the temperature as a function of r - the distance of a point from
the cylinder axis.
Since the Pennes's bio-heat equation may be applicable only for symmetrical
bodies, in many researches the human body thermal behavior was calculated using
solutions of the Pennes's bio-heat equation when parts of the human body's surface
were approximated by cylinders. In these researches, it has been found that the surface
thermal data over the body's surface calculated based on Pennes bio-heat equation are
comparable to the measured surface thermal data with compatibility of higher than
95%. In order to increase the surface thermal data accuracy's calculations, the present
method may obtain the theoretical thermal simulation by combining the actual spatial
data of the human body's surface and known predetermined thermodynamic logic (the
analytical solutions of the Pennes's bio-heat equation for symmetrical bodies in the
example herein). In these approximations, the temperature of each point on the body's
surface may be calculated by considering its spatial coordinates relative to the reference
isothermal surface as the actual spatial coordinates and setting them in the Pennes's bioheat
equation's solution. For example, when solving the Pennes's bio-heat equation of
the human's body in cylindrical coordinates, the appropriate distance of each point on
the body's surface to the reference isothermal surface is considered as r and by setting
it in the solution, the temperature at each point may be calculated. This method may
also be used for calculating approximately the temperature inside the body by
considering the spatial coordinates of each point as r, setting it in the solution and
calculating the temperature at that point. Accordingly, other analytical solutions of the
Pennes's bio-heat equation for other boundary conditions may be used for surface
thermal data calculations, such as an analytical solution for half sphere. Using this
solution, a half sphere may be fitted to the body's surface by least square techniques
and the temperature at each point of the body's surface may be defined as the analytical
calculated temperature at a suitable point with the same coordinated inside the half
sphere. In another embodiment, the analytical solutions of the Pennes's bio-heat
equation for ellipsoidal boundary conditions may be used for surface thermal data
calculations. Using this solution, a proper half ellipsoid may be fitted to the body's
surface by least square techniques and the temperature at each point of the body's
surface may be defined as the analytical calculated temperature at a suitable point with
the same coordinated inside the half ellipsoid. This method may also be used for
calculating approximately the temperature inside the body by setting the spatial
coordinates of each point in the solution and calculating the temperature at that point. A
proper half ellipsoid may also be determined by the user. By marking several points on
the body's surface, automatic software may fit the best fitted half ellipsoid to body's
surface.
After calculating the temperature map at each point of the body's surface the
method may continue to step 32 in which the temperature may be converted into grey
levels. The conversion scale may be based on a calibration target.
The next step 34 may match the calculated temperature map to the 3D model,
for example by creating a projection image of the body's surface to create the
theoretical thermal simulation (i.e. simulate the scene viewed by a thermal camera). In
this stage a correction procedure may be performed using estimated thermal
characteristics of the body of interest. Specifically, the emissivity's angular dependence
may be taken into account.
The next step 36 may compare the resulted theoretical thermal simulation of the
body's surface with the thermal image of the body's surface obtained by the IR camera.
By this comparison, a decision may be made whether or not the curved body section
has an abnormality and/or pathology such as a tumor.
The method may end at step 38.
Figure 3 shows a flowchart of another method suitable for analyzing a thermal
image of a curved body section, according to some embodiments of the present
invention. It is to be understood that several method steps appearing in the following
description or in the flowchart diagram of Figure 3 are optional and may not be
executed.
The method may begin at step 40 and continue to step 42 in which a spatial
thermal representation (also referred as an IR-spatial representation) of the curved body
section may be obtained. The IR-spatial representation, as stated, may include IR data
representing the thermal image and spatial data representing a non-planar surface of the
curved body section, where the thermal data may be associated with spatial data. This
IR-spatial representation may serve as initial boundary conditions for later calculations.
The IR-spatial representation may be generated by the method or it may be generated
by another method or system from which the IR-spatial representation may be read by
the method.
Optionally, the method may continue to step 44 in which the data in the IRspatial
representation may be preprocessed. The preprocessing may be done for the
thermal data, the spatial data, or the both spatial and thermal data.
Preprocessing of thermal data may include, without limitation, powering (e.g.,
squaring), normalizing, enhancing, smoothing and the like. Preprocessing of spatial
data may include, without limitation, removal, replacement and interpolation of pictureelements,
using various processing operations such as, but not limited to,
morphological operations (e.g., erosion, dilation, opening, closing), resizing operations
(expanding, shrinking), padding operations, equalization operations (e.g., via
cumulative density equalization, histogram equalization) and edge detection (e.g.,
gradient edge detection).
The method may continue to step 46 in which a thermal shock may be applied
to the human body.
The method may continue to step 48 which may be the first step for analytically
calculating the theoretical thermal simulation over the surface as a function of time. As
mentioned above, there are two major ways for calculating the temperature of external
body surface as a function of time; solving analytically the time dependent partial
differential heat transfer equation with the proper boundary conditions or numerically
by FDTD (Finite Differences Time Domain) calculations or other numerical
techniques. Analytical solutions for the heat transfer time dependent equation may exist
only for plane surfaces or symmetrical bodies like sphere or cylinder. For
nonsymmetrical bodies the FDTD methods should be applied. In the present approach
the theoretical thermal simulation over the surface may be calculated analytically based
on known analytical heat transfer time dependent equation solutions (also referred as
predetermined thermodynamic logic) based on behavior of a normal healthy body, the
initial thermal data and the spatial data representing a non-planar surface of the curved
body section. The first step in the calculation may be to define a reference isothermal
surface in the body. The reference isothermal surface in the body may be obtained by
virtually "removing" the actual breasts from the spatial data representing the non-planar
surface of the body section and extrapolating the surface at the vacancies using the
surrounding spatial data. The reference isothermal surface in the body may also be
obtained by approximating the surface at the vacancies with a planar surface or any
other non-planar surface. The adequate non-planar surface definition may also be
improved based on trial and error Finite Element software (e.g. ANSYS) IR-spatial
calculations.
Once the reference isothermal surface in the body is defined, the method may
continue to step 50 in which the adequate distance of each point on the body's surface
to the calculated reference isothermal surface may be determined. In general, the
appropriate distance of each point on the body's surface to the calculated reference
isothermal surface may be simply the distance between the point on the body's surface
to the nearest point on the calculated reference isothermal surface. The appropriate
distance may also be determined by any other function. It may also be improved based
on trial and error Finite Element software (e.g. ANSYS) calculations.
After the adequate distance of each point on the body's surface to the calculated
reference isothermal surface is determined, the theoretical thermal simulation over the
surface as a function of time may be calculated. In general, the calculation of a body
thermal map as a function of time may be based on predetermined thermodynamic
logic, for example the partial differential heat transfer equation with the proper human
tissue and blood thermal parameters under convective and radiative boundary
conditions. The solution of said partial differential heat transfer equation may
determine the connection between the spatial coordinates of a point in the body and its
temperature as a function of time.
Since solution for said partial differential heat transfer equation may be
applicable only for simple bodies the present method may obtain the time dependent
theoretical thermal simulation by combining the actual spatial data of the human body's
surface and known predetermined thermodynamic logic (the analytical solutions of said
partial differential heat transfer equation in the example herein). In these
approximations, the temperature of each point on the body's surface at a certain time
may be calculated by considering its spatial coordinates relative to the reference
isothermal surface as the actual spatial coordinates and setting them and the time in a
solution of said partial differential heat transfer equation. As for example, the partial
differential heat transfer equation for a plane with thickness L, under convective and
radiative boundary conditions and with initial temperature boundary conditions may be
solved analytically. The measured temperature at each surface point may be considered
as the initial temperature for the boundary conditions. The appropriate distance of each
point on the body's surface to the reference isothermal surface may be considered as L.
Setting it, the appropriate initial temperatures and the time in the solution, the
temperature at each point as a function of time may be calculated. Accordingly, other
analytical solutions of the partial differential heat transfer equation for other
geometrical bodies may be used for surface thermal data calculations, such as an
analytical solution for half sphere. Using this solution, a half sphere may be fitted to the
body's surface by least square techniques and the temperature at each point of the
body's surface may be defined as the analytical calculated temperature at a suitable
point with the same coordinated inside the half sphere as a function of time when the
measured temperature at each surface point may be considered as the initial
temperature for the boundary conditions. In another scheme the partial differential heat
transfer equation may be solved for half sphere with radius L, under convective and
radiative boundary conditions and initial temperatures boundary conditions, the
appropriate distance of each point on the body's surface to the reference isothermal
surface may be considered as L and by setting it, the initial temperature and the time in
the solution, the temperature at each point as a function of time may be calculated. In
another embodiment, the analytical solutions of partial differential heat transfer
equation for ellipsoidal body may be used for surface thermal data calculations. Using
this solution, a proper half ellipsoid may be fitted to the body's surface by least square
techniques and the temperature at each point of the body's surface as a function of time
may be defined as the analytical calculated temperature as a function of time at a
suitable point with the same coordinated inside the half ellipsoid when setting the initial
conditions in the solution.
A proper half ellipsoid may also be determined by the user. By marking several
points on the body's surface automatic software may fit the best fitted half ellipsoid to
body's surface.
After calculating the temperature map at each point of the body's surface the
method may continue to step 52 in which the temperature may be converted into grey
levels. The conversion scale may be based on a calibration target.
The next step 54 may match the calculated temperature map to the 3D model,
for example by creating a projection image of the body's surface to create the
theoretical thermal simulation (i.e. simulate the scene viewed by a thermal camera). In
this stage a correction procedure may be performed using estimated thermal
characteristics of the body of interest. Specifically, the emissivity's angular dependence
may be taken into account.
The next step 56 may compare the resulted theoretical thermal simulation (grey
levels map) of the body's surface with the measured thermal image (grey levels map) of
the body's surface obtained by the thermal camera. By this comparison a decision may
be made whether or not the body section has an abnormality and/or pathology such as a
tumor.
The method may end at step 58.
Figure 4 shows a flowchart of another method suitable for analyzing a thermal
image of a curved body section, according to some embodiments of the present
invention. It is to be understood that several method steps appearing in the following
description or in the flowchart diagram of Figure 4 are optional and may not be
executed.
The method may begin at step 60 and continue to step 62 in which a spatial
thermal representations (also referred as IR-spatial representations) of the same curved
body section of at least two persons are obtained.
Optionally, the method may continue to step 64 in which the data in the IRspatial
representation may be preprocessed. The preprocessing may be done for the
thermal data, the spatial data, or the both spatial and thermal data.
The method may continue to step 66 in which said series IR-spatial
representations of the at least two persons may be grouped into at least two groups
according to the spatial characteristics of the curved body section. Each group may
contain IR-spatial representations of body's sections with roughly the same spatial
dimensions. The phrase "same spatial characteristics" means volume, or surface's area,
or height, or length, or width, shape, etc.
The method may continue to step 68. In this step, for each group, all IR-spatial
representations may be registered and morphed by deformation software into a
representative body section. The temperature at each point at the representative body's
surface may be calculated by averaging the thermal data at the corresponding point of
all IR-spatial representations. The obtained thermal image may be considered as a
reference IR-spatial representation.
After calculating the temperature map of the reference IR-spatial representation
the method may continue to step 70 in which the temperature may be optionally
converted into grey levels. The conversion scale may be based on a calibration target.
In this stage, a correction procedure may be performed to taken into account the
emissivity's angular dependence of the surface.
Once the grey level reference IR-spatial representation of the body may be
obtained, the method may continue to step 72 in which one or series of IR-spatial
representations of an examined body section may be generated.
After generating a series of IR-spatial representations of an examined body
section, the method may continue to step 74. In this stage the examined body section
may be attributed to one of said groups according to its spatial characteristics. The body
section may be then registered and morphed by deformation software into the
representative body section of the present group.
The next step 76 may compare the resulted theoretical thermal simulation (grey levels
map) of the examined body's surface with the measured thermal image (grey levels
map) of the reference IR-spatial representation. By this comparison a decision may
made whether or not the body section has an abnormality and/or pathology such as a
tumor.
The method may end at step 78.
Figure 5 shows a flowchart of another method suitable for analyzing a thermal
image of a curved body section, according to some embodiments of the present
invention.
The method may begin at step 80 and continue to step 82 in which a spatial
thermal representations (also referred as IR-spatial representations) of the same curved
body section of at least two persons after application of thermal shock may be obtained
as a function of time.
Optionally, the method may continue to step 84 in which the data in the IRspatial
representation may be preprocessed. The preprocessing may be done for the
thermal data, the spatial data, or the both spatial and thermal data.
The method may continue to step 86 in which said series IR-spatial
representations as a function of time of the at least two persons are grouped into at least
two groups according to the spatial dimensions of the body section. Each group may
contain IR-spatial representations of body's sections with roughly the same spatial
characteristics. The phrase "same spatial characteristics" means volume, surface's area,
height, length, width, shape, etc.
The method may continue to step 88. In this step, for each group, all IR-spatial
representations may be registered and morphed by deformation software into a
representative body section. The temperature at each point at the representative body's
surface as a function of time may be calculated by averaging the thermal data at the
corresponding point and time of all IR-spatial representations. The obtained thermal
images as a function of time may be considered as a reference IR-spatial representation;
After calculating the temperature maps of the reference IR-spatial
representations as a function of time the method may continue to step 90 in which the
temperatures may be converted into grey levels. The conversion scale may be based on
a calibration target. In this stage a correction procedure may be performed to taken into
account the emissivity's angular dependence of the surface.
Once the grey level reference IR-spatial representations of the body as a
function of time may be obtained, the method may continue to step 92 in which series
of IR-spatial representations of an examined body section as a function of time may be
generated.
After generating a series of IR-spatial representations of an examined body
section, the method may continue to step 94. In this stage, the examined body section
may be attributed to one of said groups according to its spatial characteristics. The body
section may then be registered and morphed by deformation software into the
representative body section of the present group.
The next step 96 may compare the resulted theoretical thermal simulation (grey
levels map) at each certain time of the examined body's surface with the corresponding
measured thermal image (grey levels map) of the reference IR-spatial representation.
By this comparison a decision is made whether or not the body section has an
abnormality and/or pathology such as a tumor.
The method ends at step 98.
In all above-mentioned methods, there is more than one way to determine the
likelihood for the presence of a thermally distinguishable region is the body section.
In some embodiments, the difference or the ratio of the reference grey levels
map of the body's surface at different times and the measured grey levels map of the
body's surface obtained by the thermal camera in different times may be compared to
threshold values, and the comparison may be used for determining the likelihood for
the presence of a thermally distinguishable region (also referred as an abnormality).
Typically, but not obligatorily, when the difference or the ratio may be lower than the
threshold, no thermally distinguishable region is present. The threshold values might be
different for different times and different body sections.
In some embodiments, the imaging may be done in response to a cold stress test
(a test in which, merely as an example, the subject holds a cold item, somehow
changing blood flow in the body), in order to enhance the distinguish ability and thus
improve the likelihood for distinguishing an abnormality.
Moreover, in some embodiments the location and/or size and/or shape of the
abnormality (or thermally distinguishable region) inside the body may be estimated.
For example, if the temperature of the thermally distinguishable region may be known,
the region inside the body which has an approximate temperature that is comparable to
the thermally distinguishable region's temperature may be estimated as the location of
the thermally distinguishable region.
The reference grey levels map of the body's surface may be used as a platform
for any kind of comparisons to the measured grey levels map of the body's surface
obtained by the thermal camera. For example, a comparison of the integral of the grey
levels values on the reference body's surface and the integral of the grey levels values
on the measured body's surface. In another example, a comparison of the local standard
deviation of the grey levels values on the reference body's surface and the local
standard deviation of the grey levels values on the measured body's surface.
As delineated above, the calculation of the difference or the ratio of the resulted
grey levels map of the reference body's surface at different times and the measured grey
levels map of the body's surface obtained by the thermal camera in different times may
be preceded by preprocessing operation.
In some embodiments of the present invention, the preprocessing operation may
include a definition of a region-of-interest within the surface of the body section. In
these embodiments, the difference or the ratio may be calculated over the region-ofinterest.
More than one region-of-interests may be defined, in which case the surface
integral may be calculated separately for each region-of-interest. A region-of-interest
may be defined, for example, as a part of the surface which is associated with high
temperatures. A representative example of such region-of-interest may be a region
surrounding a thermally distinguishable spot on the surface. Figure 1C schematically
illustrates a thermally distinguishable spot 201. The grey area surrounding spot 201 can
be defined as a region-of-interest.
An IR-spatial representation or image may be generated obtained by acquiring
one or more thermographic images and mapping the thermographic image(s) on a
three-dimensional spatial representation.
Reference is now made to Figure 6A which shows a schematic illustration of
an IR-spatial imaging system in accordance with embodiments of the present
invention. An IR-spatial imaging system 120 is described. A living body 210 or a part
thereof of a person 212 may be located in front of an imaging device 214. Person 212
may be standing, sitting or in any other suitable position relative to imaging device
214. Person 212 may initially be positioned or later be repositioned relative to imaging
device 214 by a positioning device 215, which may typically comprise a platform
moving on a rail, by force of an engine, or by any other suitable force. Additionally, a
thermally distinguishable object 216, such as a tumor, may exist in body 210 of person
212. For example, when body 210 comprises a breast, object 216 may be a breast
tumor such as a cancerous tumor.
In accordance with an embodiment of the present invention, person 212 may be
wearing a clothing garment 218, such as a shirt. Clothing garment 218 may be nonpenetrable
or partially penetrable to visible wavelengths such as 400-700 nanometers,
and may be penetrable to wavelengths that are longer than visible wavelengths, such as
infrared wavelengths. Additionally, a reference mark 220 may be located close to
person 212, optionally directly on the body of person 212 and in close proximity to
body 210. Optionally, reference mark 220 may be directly attached to body 210.
Reference mark 220 may typically comprise a piece of material, a mark drawn on
person 212 or any other suitable mark, as described herein below.
Imaging device 214 may typically comprise at least one visible light imaging
device 222 that may sense at least visible wavelengths and at least one thermographic
imaging device 224 which may be sensitive to infrared wavelengths, typically in the
range of as 3-5 micrometer and/or 8-12 micrometer. Typically imaging devices 222
and 224 may be capable of sensing reference mark 220 described hereinabove.
Optionally, a polarizer 225 may be placed in front of visible light imaging
device 222. As a further alternative, a color filter 226, which may block at least a
portion of the visible wavelengths, may be placed in front of visible light imaging
device 222.
Typically, at least one visible light imaging device 222 may comprise a blackand-
white or color stills imaging device, or a digital imaging device such as CCD or
CMOS. Additionally, at least one visible light imaging device 222 may comprise a
plurality of imaging elements, each of which may be a three-dimensional imaging
element.
Optionally, imaging device 214 may be repositioned relative to person 212 by a
positioning device 227. As a further alternative, each of imaging devices 222 and 224
may also be repositioned relative to person 212 by at least one positioning device 228.
Positioning device 227 may comprise an engine, a lever or any other suitable force,
and may also comprise a rail for moving imaging device 214 thereon. Repositioning
device 228 may be similarly structured.
Data acquired by visible light imaging device 222 and thermographic imaging
device 224 may be output to a data processor 230 via a communications network 232,
and may be typically analyzed and processed by an algorithm running on the data
processor. The resulting data may be displayed on at least one display device 234,
which is optionally connected to data processor 230 via a communications network
236. Data processor 230 may typically comprise a PC, a PDA or any other suitable
hardware data processor. Communications networks 232 and 236 may typically
comprise a physical communications network such as an internet or intranet, or may
alternatively comprise a wireless network such as a cellular network, infrared
communication network, a radio frequency (RF) communications network, a bluetooth
(BT) communications network or any other suitable communications network.
In accordance with an embodiment of the present invention, display 234
typically comprises a screen, such as an LCD screen, a CRT screen or a plasma screen.
As a further alternative display 234 may comprise at least one visualizing device
comprising two LCDs or two CRTs, located in front of a user's eyes and packaged in a
structure similar to that of eye-glasses. Display 234 may also display a pointer 238,
which may be typically movable along the X, Y and Z axes of the displayed model and
may be used to point to different locations or elements in the displayed data.
Reference is now made to Figures 6B-C and 7A-E which show illustrations of
various operation principles of IR-spatial imaging system, in accordance with various
exemplary embodiments of the invention.
The visible light imaging is described first, with reference to Figures 6B-C, and
the thermographic imaging is described hereinafter, with reference to figures 7A-E. It
will be appreciated that the visible light image data acquisition described in Figures
6B-C may be performed before, after or concurrently with the thermographic image
data acquisition described in Figures 7A-E.
Referring to Figures 6B-C, person 212 comprising body 210 may be located on
positioning device 215 in front of imaging device 214, in a first position 240 relative to
the imaging device. First image data of body 210 may be acquired by visible light
imaging device 222, optionally through polarizer 225 or as an alternative option
through color filter 226. The advantage of using a color filter is that it may improve the
signal-to-noise ratio, for example, when the person is illuminated with a pattern or
mark of specific color, the color filter may be used to transmit only the specific color
thereby reducing background readings. Additionally, at least second image data of
body 210 is acquired by visible light imaging device 222, such that body 210 may be
positioned in at least a second position 242 relative to imaging device 214. Thus, the
first, second and optionally more image data may be acquired from at least two
different viewpoints of the imaging device relative to body 210.
The second relative position 242 may be configured by repositioning person
212 using positioning device 215 as seen in Figure 6B, by repositioning imaging
device 214 using positioning device 227 as seen in Figure 6C or by repositioning
imaging device 222 using positioning device 228 as seen in Figure 6C. As a further
alternative, second relative position 242 may be configured by using two separate
imaging devices 214 as seen in Figure 7D or two separate visible light imaging device
222 as seen in Figure 7E (with devices 224).
Referring to Figures 7A-E, person 212 comprising body 210 may be located on
positioning device 215 in front of imaging device 214, in a first position 244 relative to
the imaging device. First thermographic image data of body 210 may be acquired by
thermographic imaging device 224. Optionally, at least second thermographic image
data of body 210 may be acquired by thermographic imaging device 224, such that
body 210 may be positioned in at least a second position 246 relative to imaging
device 214. Thus, the first, second and optionally more thermographic image data may
be acquired from at least two different viewpoints of the thermographic imaging
device relative to body 210.
The second relative position 246 may be configured by repositioning person
212 using positioning device 215 as seen in Figure 7A, by repositioning imaging
device 214 using positioning device 227 as seen in Figure 7B, or by repositioning
thermographic imaging device 224 using positioning device 228 as seen in Figure 7C.
As a further alternative, second relative position 246 may be configured by using two
separate imaging devices 214 as seen in Figure 7D or two separate thermographic
imaging devices 224 as seen in Figure 7E.
Image data of body 210 may be acquired by thermographic imaging device
224, by separately imaging a plurality of narrow strips of the complete image of body
210. Alternatively, the complete image of body 210 may be acquired by the
thermographic imaging device, and the image may be sampled in a plurality of narrow
strips or otherwise shaped portions for processing. As a further alternative, the imaging
of body 210 may be performed using different exposure times.
The thermographic and visible light image data obtained from imaging device
214 may be analyzed and processed by data processor 230 as follows. Image data
acquired from imaging device 222 may be processed by data processor 230 to build a
three-dimensional spatial representation of body 210, using algorithms and methods
that are well known in the art, such as the method described in U.S. Patent No.
6,442,419 which is hereby incorporated by reference as if fully set forth herein. The
three-dimensional spatial representation may comprise the location of reference marker
220 (cf. Figure 6A). Optionally, the three-dimensional spatial representation may
comprise information relating to the color, hue and tissue texture of body 210.
Thermographic image data acquired from imaging device 224 may be processed by
data processor 230 to build a thermographic three-dimensional model of body 210,
using algorithms and methods that are well known in the art, such as the method
described in U.S. Patent No. 6,442,419. The thermographic three-dimensional model
may comprise reference marker 220 (cf. Figure 7A). The thermographic threedimensional
model may then be mapped by processor 230 onto the three-dimensional
spatial representation, e.g., by aligning reference marker 220, to form the IR-spatial
image.
Reference is now made to Figs. 8A, 8B and 8C, which show pictorial views of
a spatial thermal representation 800, a theoretical thermal simulation 802 and a
comparison 804, respectively - all of a healthy subject having no breast abnormalities
(e.g. tumors). Representation 800 and simulation 802 are shown as a heat map,
wherein darker areas mean lower temperature whereas lighter areas mean higher
temperature. The heat map is displayed on a scale of 29 to 34 degrees Celsius.
As can be observed in Fig. 8A, spatial thermal representation 800 includes
areas of different temperature which are randomly located, sized and shaped - as
acquired in reality by the present imaging device. In contrast, theoretical thermal
simulation 802 of Fig. 8B is shown with smoother and far more arranged temperature
gradients. That is, theoretical thermal simulation 802 represents a mathematical model
of temperature gradients of a 3D reconstruction of that patient's breasts.
Comparison 804 of Fig. 8C shows temperature differences between spatial
thermal representation 800 and theoretical thermal simulation 802. As can be
observed, the majority of the area of comparison 804 is indicative of a temperature
difference of approximately 0 to 0.5 degrees Celsius, whereas the remaining area
indicates a temperature difference of approximately 1-1.5 degrees Celsius. Namely,
comparison 804 indicates that the temperature differences are relatively minimal.
Reference is now made to Figs. 9A, 9B and 9C, which show pictorial views of
a spatial thermal representation 900, a theoretical thermal simulation 902 and a
comparison 904, respectively - all of a sick subject having breast abnormalities (e.g.
tumors). Representation 900 and simulation 902 are shown as a heat map, wherein
darker areas mean lower temperature whereas lighter areas mean higher temperature.
The heat map is displayed on a scale of 26 or 27 to 34 degrees Celsius.
As can be observed in Fig. 9A, spatial thermal representation 900 includes
areas of different temperature which are randomly located, sized and shaped - as
acquired in reality by the present imaging device. In contrast, theoretical thermal
simulation 902 of Fig. 9B is shown with smoother and far more arranged temperature
gradients. That is, theoretical thermal simulation 902 represents a mathematical model
of temperature gradients of a 3D reconstruction of that patient's breasts.
Comparison 904 of Fig. 9C shows temperature differences between spatial
thermal representation 900 and theoretical thermal simulation 902. As can be
observed, the majority of the area of comparison 904 is indicative of a temperature
difference of approximately 2.5 to 5 degrees Celsius, whereas the remaining area
indicates a temperature difference of approximately 0 to 1.5 degrees Celsius. Namely,
comparison 804 indicates that the temperature differences are significant.
In sum, significant temperature differences between a spatial thermal
representation and a theoretical thermal simulation, both in 3D, may be indicative,
where they appear, of an abnormality such as one or more tumors. In some
embodiments, a user may set a temperature difference threshold, above which the
method alerts of the possible existence of an abnormality. The threshold may
optionally pertain also to a size of an area of that temperature difference, to filter out
areas which are either too small or too large to represent a real abnormality.
It should be understood that the above mentioned embodiments may be applied
for determining the likelihood of the presence of a thermally distinguishable object in
any object, based on said comparisons.
The terms "comprises", "comprising", "includes", "including", "having" and
their conjugates mean "including but not limited to".
As used herein, the singular form "a", "an" and "the" include plural references
unless the context clearly dictates otherwise. For example, the term "a compound" or
"at least one compound" may include a plurality of compounds, including mixtures
thereof.
Throughout this application, various embodiments of this invention may be
presented in a range format. It should be understood that the description in range format
is merely for convenience and brevity and should not be construed as an inflexible
limitation on the scope of the invention. Accordingly, the description of a range should
be considered to have specifically disclosed all the possible subranges as well as
individual numerical values within that range. For example, description of a range such
as from 1 to 6 should be considered to have specifically disclosed subranges such as
from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well
as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies
regardless of the breadth of the range.
Whenever a numerical range is indicated herein, it is meant to include any cited
numeral (fractional or integral) within the indicated range. The phrases "ranging/ranges
between" a first indicate number and a second indicate number and "ranging/ranges
from" a first indicate number "to" a second indicate number are used herein
interchangeably and are meant to include the first and second indicated numbers and all
the fractional and integral numerals therebetween.
It is appreciated that certain features of the invention, which are, for clarity,
described in the context of separate embodiments, may also be provided in combination
in a single embodiment. Conversely, various features of the invention, which are, for
brevity, described in the context of a single embodiment, may also be provided
separately or in any suitable subcombination or as suitable in any other described
embodiment of the invention. Certain features described in the context of various
embodiments are not to be considered essential features of those embodiments, unless
the embodiment is inoperative without those elements.
Although the invention has been described in conjunction with specific
embodiments thereof, it is evident that many alternatives, modifications and variations
will be apparent to those skilled in the art. Accordingly, it is intended to embrace all
such alternatives, modifications and variations that fall within the spirit and broad
scope of the appended claims.
All publications, patents and patent applications mentioned in this specification
are herein incorporated in their entirety by reference into the specification, to the same
extent as if each individual publication, patent or patent application was specifically
and individually indicated to be incorporated herein by reference. In addition, citation
or identification of any reference in this application shall not be construed as an
admission that such reference is available as prior art to the present invention. To the
extent that section headings are used, they should not be construed as necessarily
limiting.
CLAIMS
What is claimed is:
1. An imaging method comprising:
receiving a spatial thermal representation of a curved body section, wherein the
spatial thermal representation comprises a thermal image associated with spatial
data; and
generating a theoretical thermal simulation of the curved body section, wherein
said generating of the theoretical thermal simulation is based on the spatial data of
the representation and on predetermined thermodynamic logic of a type of the
curved body section.
2. The method according to claim 1, further comprising comparing the spatial
thermal representation and the theoretical thermal simulation.
3. The method according to claim 2, further comprising detecting an abnormality
in the curved body section, wherein said detecting is based on said comparing of the
spatial thermal representation and the theoretical thermal simulation.
4. The method according to claim 3, further comprising back-solving a parameter
of the abnormality inside the curved body section.
5. The method according to claim 4, wherein said back-solving comprises:
generating a plurality of additional theoretical thermal simulations of a
theoretical tumor inside the curved body section, wherein, in each simulation of the
plurality of additional theoretical thermal simulations, a parameter of the theoretical
tumor is adjusted; and
comparing the spatial thermal representation and the plurality of additional
theoretical thermal simulations, to determine which simulation of the plurality of
additional theoretical thermal simulations is closest to the representation.
6. The method according to any one of claims 4 and 5, wherein the parameter of
the abnormality is selected from the group consisting of: a location of the abnormality
inside the curved body section, a size of the abnormality, a shape of the abnormality,
and a type of the abnormality.
7. The method according to claim 3, wherein said spatial thermal representation is
responsive to a cold stress test.
8. The method according to claim 7, wherein the predetermined thermodynamic
logic is under an influence of a theoretical cold stress test.
9. The method according to claim 1, wherein the predetermined thermodynamic
logic of the type of the curved body section is computed based on healthy subjects.
10. The method according to any one of claims 1 to 9, wherein the curved body
section comprises one or more breasts.
11. An imaging system comprising:
an imaging device; and
a hardware data processor configured to:
(a) generate a spatial thermal representation of a curved body section, wherein
the spatial thermal representation comprises a thermal image associated with spatial
data, and
(b) generate a theoretical thermal simulation of the curved body section,
wherein said generate of the theoretical thermal simulation is based on the spatial
data of the representation and on predetermined thermodynamic logic of a type of
the curved body section.
12. The imaging system according to claim 11, wherein said hardware data
processor is further configured to compare the spatial thermal representation and the
theoretical thermal simulation.
13. The imaging system according to claim 12, wherein said hardware data
processor is further configured to detect an abnormality in the curved body section,
wherein said detect is based on said comparing of the spatial thermal representation
and the theoretical thermal simulation.
14. The imaging system according to claim 13, wherein said hardware data
processor is further configured to back- solve a parameter of the abnormality inside the
curved body section.
15. The imaging system according to claim 14, wherein said back-solve comprises:
generating a plurality of additional theoretical thermal simulations of a
theoretical tumor inside the curved body section, wherein, in each simulation of the
plurality of additional theoretical thermal simulations, a parameter of the theoretical
tumor is adjusted; and
comparing the spatial thermal representation and the plurality of additional
theoretical thermal simulations, to determine which simulation of the plurality of
additional theoretical thermal simulations is closest to the representation.
16. The imaging system according to any one of claims 14 and 15, wherein the
parameter of the abnormality is selected from the group consisting of: a location of the
abnormality inside the curved body section, a size of the abnormality, a shape of the
abnormality and a type of the abnormality.
17. The imaging system according to claim 13, wherein said spatial thermal
representation is responsive to a cold stress test, thereby enhancing a contrast between
the abnormality and a normal tissue adjacent to the abnormality.
18. The imaging system according to claim 17, wherein the predetermined
thermodynamic logic is under an influence of a theoretical cold stress test.
19. The imaging system according to claim 11, wherein the predetermined
thermodynamic logic of the type of the curved body section is computed based on
healthy subjects.
20. The imaging system according to any one of claims 1 1 to 19, wherein the
curved body section comprises one or more breasts.
21. The imaging system according to any one of claims 1 1 to 19, wherein said
imaging device comprises a thermal imaging device and a visible light imaging device.
22. An imaging method comprising:
receiving spatial data of a curved body section; and
generating a theoretical thermal simulation of the curved body section, wherein
said generating of the theoretical thermal simulation is based on the spatial data of
the representation and on predetermined thermodynamic logic of a type of the
curved body section.
23. The method according to claim 22, further comprising receiving a spatial
thermal representation of the curved body section, wherein the spatial thermal
representation comprises said spatial data and a thermal image associated with said
spatial data.
24. The method according to claim 23, further comprising comparing the spatial
thermal representation and the theoretical thermal simulation.
25. The method according to claim 24, further comprising detecting an
abnormality in the curved body section, wherein said detecting is based on said
comparing of the spatial thermal representation and the theoretical thermal simulation.
26. The method according to claim 35, further comprising back-solving a
parameter of the abnormality inside the curved body section.
27. The method according to claim 26, wherein said back-solving comprises:
generating a plurality of additional theoretical thermal simulations of a
theoretical tumor inside the curved body section, wherein, in each simulation of the
plurality of additional theoretical thermal simulations, a parameter of the theoretical
tumor is adjusted; and
comparing the spatial thermal representation and the plurality of additional
theoretical thermal simulations, to determine which simulation of the plurality of
additional theoretical thermal simulations is closest to the representation.
28. The method according to any one of claims 26 and 27, wherein the parameter
of the abnormality is selected from the group consisting of: a location of the
abnormality inside the curved body section, a size of the abnormality, a shape of the
abnormality, and a type of the abnormality.
29. The method according to claim 25, wherein said spatial thermal representation
is responsive to a cold stress test.
30. The method according to claim 29, wherein the predetermined thermodynamic
logic is under an influence of a theoretical cold stress test.
31. The method according to claim 22, wherein the predetermined thermodynamic
logic of the type of the curved body section is computed based on healthy subjects.
32. The method according to any one of claims 22 to 31, wherein the curved body
section comprises one or more breasts.