•
•
BACKGROUND OF THE INVENTION
The subject matter disclosed herein relates generallyto imaging systems, and
more particularly to methods and system for displaying segmented images.
Segmentation is commonly used to outline objects and/or regions within
three-dimensional (3D) image volumes. For example, 3D image volumes may be segmented
for surgical planning, for radiation planning, and/or for general object identification.
Typically, at least some of the segmented slices are displayed as two-dimensional (2D)
images. However, viewing the 2D images or slices of the segmented volume to ascertain a
size or dimension of the object may be tedious and time consuming.
For example, a single 2D image may be for example, approximately 3mm
thick. For a focal tumor, looking at the segmentation in the plane defined by the location of
the tumor may be sufficient to enable the user to perform surgical planning, radiation
planning, and/or for general object identification. For an extended tumor or a tumor having
an ill-defined shape, the tumor may extend beyond the boundaries of the tumor shown in the
single 2D image. More specifically, the user may view the single 2D image and assume that
the full extent of the tumor is shown. However, the tumor may appear to be smaller, larger,
or have a different shape in different 2D images in parallel planes. If the full extent of the
segmentation is not manually checked by the user in all planes that contain tumor as defined
by the segmentation, there is a potential for error in reporting of, for example, the tumor
mean value and/or the tumor volume. Further, the maximum value of the tumor may be
defined by a nearby high-uptake structure and not actually within the tumor itself.
Accordingly, to verify the full extent of the tumor, and perform analysis of the tumor, the
user typically displays and reviews numerous 2D images. However, manually displaying and
reviewing numerous 2D images is time consuming. Moreover, the difficulty and tediousness
of displaying numerous 2D images, one at a time, may require a greater amount of user input
than is desired.
2
•
,
BRIEF DESCRIPTION OF THE INVENTION
In one embodiment, a method for displaying a segmented two-dimensional
(2D) image is provided. The method includes obtaining a three-dimensional (3D) volume
dataset corresponding to an imaged volume along a viewing plane, segmenting an object of
interest within 3D volume to generate a plurality of segmented two-dimensional (2D) images
along the viewing plane, selecting a reference image from the plurality of segmented 2D
images, and displaying the reference image, the reference image having a first segmentation
boundary drawn around the object of interest and a second segmentation boundary drawn
around the object of interest, the first segmentation boundary being derived from the
segmentation performed on the reference image in the viewed plane and the second
segmentation boundary being derived from the segmentation performed on at least one nonreference
image not in the currently-viewed plane ofthe plurality of segmented 2D images.
In another embodiment, a system for displaying a segmented 2D image is
provided. The system includes a medical imaging scanner, and a computer coupled to the
medical imaging scanner. The computer is configured to obtain a three-dimensional (3D)
volume dataset corresponding to an imaged volume along a viewing plane from the medical
imaging scanner, segment an object of interest within 3D volume to generate a plurality of
segmented two-dimensional (2D) images along the viewing plane, receive an input selecting
a reference image from the plurality of segmented 2D images, and automatically display the
reference image, the reference image having a first segmentation boundary drawn around the
object of interest and a second segmentation boundary drawn around the object of interest,
the first segmentation boundary being derived from the segmentation performed on the
reference image and the second segmentation boundary being derived from the segmentation
performed on at least one non-reference image of the plurality of segmented 2D images.
In a further embodiment, a non-transitory computer readable medium is
provided. The non-transitory computer readable medium is encoded with a program
programmed to instruct a computer to obtain a three-dimensional (3D) volume dataset
corresponding to an imaged volume along a viewing plane from the medical imaging scanner,
3
segment an object of interest within 3D volume to generate a plurality of segmented twodimensional
(2D) images along the viewing plane, receive an input selecting a reference
image from the plurality of segmented 2D images, and automatically display the reference
image, the reference image having a first segmentation boundary drawn around the object of
interest and a second segmentation boundary drawn around the object of interest, the first
segmentation boundary being derived from the segmentation performed on the reference
image and the second segmentation boundary being derived from the segmentation
performed on at least one non-reference image of the plurality of segmented 2D images.
BRIEF DESCRIPTION OF THE DRAWINGS
• Figure 1 is a pictorial view of an exemplary imaging system formed in
accordance with various embodiments.
Figure 2 is a flowchart illustrating a method for displaying an image in
accordance with various embodiments.
Figure 3 is block diagram of an exemplary dataset that may be acquired in
accordance with various embodiments.
Figure 4 is a plurality of images that may be displayed in accordance with
various embodiments.
Figure 5 is a plurality ofviewports that may be generated in accordance with
• various embodiments.
Figure 6 is another plurality of images that may be displayed in accordance
with various embodiments.
Figure 7 is still another plurality of images that may be displayed in
accordance with various embodiments.
Figure 8 are a plurality of viewports that may be generated in accordance
with various embodiments.
4
•
,
Figure 9 is a block schematic diagram of the second modality unit shown in
Figure 1 in accordance with various embodiments.
DETAILED DESCRIPTION OF THE INVENTION
The foregoing summary, as well as the following detailed description of
various embodiments, will be better understood when read in conjunction with the appended
drawings. To the extent that the figures illustrate diagrams of the functional blocks of the
various embodiments, the functional blocks are not necessarily indicative of the division
between hardware circuitry. Thus, for example, one or more of the functional blocks (e.g.,
processors or memories) may be implemented in a single piece of hardware (e.g., a general
purpose signal processor or a block of random access memory, hard disk, or the like) or
multiple pieces of hardware. Similarly, the programs may be stand alone programs, may be
incorporated as subroutines in an operating system, may be functions in an installed software
package, and the like. It should be understood that the various embodiments are not limited
to the arrangements and instrumentality shown in the drawings.
As used herein, an element or step recited in the singular and proceeded with
the word "a" or "an" should be understood as not excluding plural of said elements or steps,
unless such exclusion is explicitly stated. Furthermore, references to "one embodiment" of
the present invention are not intended to be interpreted as excluding the existence of
additional embodiments that also incorporate the recited features. Moreover, unless
explicitly stated to the contrary, embodiments "comprising" or "having" an element or a
plurality of elements having a particular property may include additional elements not having
that property.
Also as used herein, the phrase "reconstructing an image" is not intended to
exclude embodiments in which data representing an image is generated, but a viewable image
is not. Therefore, as used herein the term "image" broadly refers to both viewable images
and data representing a viewable image. However, many embodiments generate, or are
configured to generate, at least one viewable image.
Described in various embodiments herein is an Advanced Tumor Layout and
Summary (ATLaS) module 50. In some embodiments, the ATLaS module 50 is configured
5
•
to obtain a 3D volume data set corresponding to an imaged volume, the 3D volume dataset
including a plurality of slices acquired along a plane, position a 3D bounding box around an
object of interest in the 3D volume data set, segment the object of interest within the
bounding box to generate a plurality of slices of the object of interest along the plane, and
display a two-dimensional (2D) image of a first slice, the 2D image having a first
segmentation boundary drawn around the object of interest in the first slice and a second
segmentation boundary drawn around the object of interest in a second different slice.
The ATLaS module 50 may be utilized with an imaging system such as the
imaging system 10 as shown in Figure 1. In various embodiments, the imaging system lOis
a multi-modality imaging system that includes different types of imaging modalities, such as
Positron Emission Tomography (PET), Single Photon Emission Computed Tomography
(SPECT), Computed Tomography (CT), ultrasound, Magnetic Resonance Imaging (MRI) or
any other system capable of generating diagnostic images.
In the illustrated embodiment, the imaging system 10 is a CTIPET system. It
should be realized that the various embodiments are not limited to multi-modality medical
imaging systems, but may be used on a single modality medical imaging system such as a
stand-alone CT imaging system or a stand-alone PET system, for example. Moreover, the
various embodiments are not limited to medical imaging systems for imaging human
subjects, but may include veterinary or non-medical systems for imaging non-human objects,
etc.
• Referring to Figure 1, the multi-modality imaging system 10 includes a first
modality unit 12 and a second modality unit 14. In the illustrated embodiment, the first
modality unit 12 is a CT imaging system and the second modality unit is a PET system. The
two modality units enable the multi-modality imaging system 10 to scan an object or subject
16 in a first modality using the first modality unit 12 and to scan the subject 16 in a second
modality using the second modality unit 14. The multi-modality imaging system 10 allows
for multiple scans in different modalities to facilitate an increased diagnostic capability over
single modality systems.
6
•
•
The imaging system lOis shown as including a gantry 18 that is associated
with the first modality unit 12 and a gantry 20 that is associated with the second modality unit
14. During operation, the subject 16 is positioned within a central opening 22, defined
through the imaging system 10, using for example, a motorized table 24. An x-ray source 26
projects a beam of x-rays through the subject 16. After being attenuated by the subject 16,
the x-rays impinge on a detector 28 located on the opposite side ofthe gantry 18.
The imaging system 10 also includes an operator workstation 30. During
operation, the motorized table 24 moves the subject 16 into the central opening 22 of the
gantry 18 and/or the gantry 20 in response to one or more commands received from the
operator workstation 30. The workstation 30 then operates the first and/or second modality
units 12 and 14 to both scan the subject 16 and to acquire an attenuation projection data set
32 and/or an emission image dataset 34. The workstation 30 may be embodied as a personal
computer (PC) that is positioned near the imaging system 10 and hard-wired to the imaging
system 10 via a communication link 36. The workstation 30 may also be embodied as a
portable computer such as a laptop computer or a hand-held computer that transmits
information to, and receives information from the imaging system 10. Optionally, the
communication link 36 may be a wireless communication link that enables information to be
transmitted to and/or from the workstation 30 to the imaging system 10 wirelessly. In
operation, the workstation 30 is configured to control the operation of the imaging system 10
in real-time. The workstation 30 is also programmed to perform medical image diagnostic
acquisition and reconstruction processes described herein.
The operator workstation 30 includes a central processing unit (CPU) or
computer 40, a display 42, and an input device 44 (e.g., a mouse, and/or a keyboard). As
used herein, the term "computer" may include any processor-based or microprocessor-based
system including systems using microcontrollers, reduced instruction set computers (RISC),
application specific integrated circuits (ASICs), field programmable gate array (FPGAs),
logic circuits, and any other circuit or processor capable of executing the functions described
herein. The above examples are exemplary only, and are thus not intended to limit in any
way the defmition and/or meaning of the term "computer". In the exemplary embodiment,
the computer 40 executes a set of instructions that are stored in one or more storage elements
or memories, in order to process information received from the first and second modality
7
•
units 12 and 14. The storage elements may also store data or other information as desired or
needed. The storage element may be in the form of an information source or a physical
memory element located within the computer 40.
The imaging system 10 also includes the ATLaS module 50 that is
configured to implement various methods described herein. The ATLaS module 50 may be
implemented as a piece of hardware that is installed in the computer 40. Optionally, the
ATLaS module 50 may be implemented as a set of instructions that are installed on the
computer 40. The set of instructions may be stand alone programs, may be incorporated as
subroutines in an operating system installed on the computer 40, may be functions in an
installed software package on the computer 40, and the like. It should be understood that the
various embodiments are not limited to the arrangements and instrumentality shown in the
drawings.
Figure 2 is a flowchart of an exemplary method 100 for displaying a 20
image of an object of interest. In various embodiments, the method 100 may be implemented
using for example, the ATLaS module 50. At 102, an emission image dataset, such as the
emission imag~ dataset 34 is acquired. The emission image dataset 34 is a three-dimensional
(3D) volume of information (as shown in Figure 3) having a plurality of image voxels
corresponding to image data. It should be noted that the 3D emission image dataset 34 is
generally formed from a plurality of 20 image slices arranged in a stack. For example, as
shown in Figure 3, the emission image dataset 34 may be formed from a plurality of slices
200, including a first slice 202, a second slice 204, a third slice 206, and an nth slice 208. It
should be realized that the emission image dataset 34 may be utilized to form a plurality of
slices in three orthogonal axes. For example, the emission image dataset 34 may include a
plurality of slices along a first axis to form a sagittal view of the subject 16, a plurality of
slices along a second axis to form an axial view of the subject 16, and a plurality of slices
along a third axis to form a coronal view ofthe subject 16.
In operation, to generate the emission image dataset 34, the imaging system
10 performs a scan of, for example, the subject 16. In various embodiments, the imaging
system lOis configured to perform a scan of a region of interest that includes, for example, a
tumor or lesion. Emission image dataset 34, as used herein, is a set of 3D data that is
8
•
•
represented by three orthogonal axes acquired over a predetennined time period of, for
example, the tumor and at least some of the regions surrounding the tumor. It should be
realized that although various embodiments are described with respect to imaging a tumor,
the various embodiments may also be utilized to image other objects or organs and the tumor
is an example of one such object.
At 104, the emission image dataset 34 is processed, or rendered, to generate
at least one 2D image or slice of the subject 16. In various embodiments, the emission image
dataset 34 is processed, or rendered, to generate a plurality of 2D images or slices of the
subject 16. For example, Figure 4 is a pictorial view of an exemplary 2D axial image 300, a
2D sagittal image 302, and a 2D coronal image 304 that may be rendered at 104. It should be
realized that because the emission image dataset 34 is acquired along three orthogonal axes,
that the emission image dataset 34 includes an axial volume of emission information that may
be utilized to construct a plurality of axial 2D images 310, wherein the 2D axial image 300
represents one such image. Moreover, the emission image dataset 34 includes a sagittal
volume of emission information that may be utilized to construct a plurality of sagittal 2D
images 312 wherein the 2D sagittal image 302 represents one such image, and the emission
image dataset 34 includes a coronal volume of emission information that may be utilized to
construct a plurality of coronal 2D images 314, wherein the 2D coronal image 304 represents
one such image. Accordingly, the emission image dataset 34 may be utilized to render a
plurality of slices in three orthogonal axes which may then be utilized to generate a plurality
of 2D images.
In various embodiments, at least a portion of the emission image dataset 34
may rendered based on 3D rendering settings. By rendering "at least a portion" of the
emission image dataset 34, it is meant that the entire emission image dataset 34 or a subset of
the emission image dataset 34 may be rendered, for example, such that an image is
reconstructed or formed from the data. The 3D rendering settings used to render the emission
image dataset 34 detennine how one or more images ofthe emission image dataset 34 will be
viewed by a user. The 3D rendering settings may include, but are not limited to, orientation,
the type of renderer (e.g., volume rendering, maximum intensity projection (MIP), etc.), a
depth setting, a clipping setting, a thickness setting, an opacity map, and/or the like.
9
,
,
Referring again to Figure 2, at 106, at least one of the rendered 20 images, 300, 302, and/or
304 is then displayed based on the 30 rendering settings.
At 108, a bounding box 332 is positioned around an object of interest that is
to be segmented. More specifically, in some embodiments, a 20 segmentation may be
manually performed by the user by drawing or virtually tracing on a screen a bounding box
332 (shown in Figure 4) that encloses an object or region 330 the user desires to be
segmented from the emission image dataset 34. For example, as shown in Figure 4, the user
may draw the bounding box 332 around the tumor 330 using an input device, such as, but not
limited to, a mouse, a touch pad, a pointer, a stylist, and/or the like. In other embodiments,
the 20 segmentation may be performed semi-automatically or fully-automatically using a
computer (e.g., the computer 40 shown in Figure 1). For example, when the 20 segmentation
is semi-automatically created, the user may position a seed point (not shown) on the tumor
330, the computer 40 may then create the 20 segmentation (e.g., using a live-wire-based
segmentation, seeded watershed segmentation, and/or the like). One example of fully
automatic 20 segmentation using a computer includes, but is not limited to, automatic
thresholding. In various embodiments, the user may modify the bounding box 332 with the
input device 44, such as to change a size or position relative to the tumor 330 as is described
in more detail below.
Referring again to Figure 2, at 110, a 20 segmentation of at least one of the
rendered 20 images 300, 302, and/or 304 is performed based on the bounding box 332
described above. In various embodiments, and referring again to Figure 4, the object of
interest selected to be segmented is the tumor 330. The 20 segmentation of a rendered 30
volume data, such as the 20 axial image 300, may be created using any suitable method,
process, means, structure, and/or the like.
In operation, the segmentation may be performed using a segmentation
algorithm. The segmentation algorithm uses a principle, whereby it is generally assumed that
various organs, tissue, fluid, and other anatomical features, surrounding the tumor 330 may
be differentiated from the tumor 330 by determining the intensity of each voxe1 in the image
data. The intensity generally represents the value of the voxel. Based on the intensity values
of each of the voxels, the tumor 330 may be distinguished from the other anatomical features.
10
Accordingly, at 110 the segmentation algorithm is configured to automatically compare the
intensity value for each voxel in the emission image dataset 34 to a predetermined intensity
value, using for example, a thresholding process. In the exemplary embodiment, the
predetermined intensity value may be a range of predetermined intensity values. The
predetermined value range may be automatically set based on a priori information of the
tumor 330. Optionally, the predetermined range may be manually input by the operator. In
one embodiment, if the intensity value of a voxel is within the predetermined range, the voxel
is classified as belonging to the tumor 330. Otherwise, the voxel is classified as not
belonging to the tumor 330. It should be realized that the segmentation algorithm may also
be utilized with other segmentation techniques to identify the tumor 330. Additionally, as
• should be appreciated, other suitable segmentation algorithms may be used.
At 112, the segmented information of the tumor 330 identified at 110 is
utilized to generate and display at least one 2D image of the segmented tumor 330. For
example, Figure 5 illustrates a plurality of exemplary 2D surface renderings of the tumor 330
that may be generated and displayed using the information acquired at 110. In various
embodiments, the ATLaS module 50 is configured to display a plurality of segmented 2D
images concurrently with the associated 2D image utilized to perform the segmentation. For
example, in various embodiments, the 2D axial image 300 may be displayed concurrently
with a 2D segmented axial image 340, the 2D sagittal image 302 may be displayed
concurrently with a 2D segmented sagittal image 342, and the 2D coronal image 304 may be
displayed concurrently with a 2D segmented coronal image 344. It should be realized that the
• segmented images 340, 342, 344 may also be shown separately from the 2D images 300, 302,
304. Moreover, it should be realized that a single segmented image may be shown with a
single non-segmented image.
In various embodiments, the segmented images 340, 342, and 344 are
displayed in different viewports. A viewport, as used herein, is a framed area on a display,
such as the display 42, for viewing information. Accordingly, in various embodiments, the
segmented axial image 340 is displayed in a viewport 350, the segmented sagittal image 342
is displayed in a viewport 352, and the segmented coronal image 344 is displayed in a
viewport 354. In operation, the viewports 350, 352, and 354 enable the operator to
manipulate various portions of the segmented images. For example, as shown in Figure 5,
11
the viewports 350, 352, and 354 each display a magnified and/or rotatable image of the
segmented tumor 330. In various embodiments, the viewports 350, 352, and 354 enable the
user to modify a location of the bounding box 332. For example, the viewport 350 includes
an icon 360 that enables the user to move the bounding box 332 up one voxel per click and an
icon 362 that enables the user to move the bounding box 332 down one voxel per click.
Alternatively, the icons 360 and 362 can be configured to change the size of the bounding
box up and down by clicking. The viewports 352 and 354 also include the same icons to
enable the user to modify the location of the bounding boxes 332 shown in the viewports,
respectively. Accordingly, in one embodiment, the user may utilize the icons 360 and 362 to
modify the size of the bounding box 332. In other embodiments, the user may select the
• bounding box 332, using for example a mouse, and manually modify the size, shape or
location of the bounding box 332 using the mouse.
•
As shown in Figure 5, the viewports 350, 352, and 354 also include visual
indicators, referred to herein as segmentation boundaries, that depict or encapsulate the object
being segmented, e.g. the tumor 330. It should be realized that the area within the
segmentation boundary includes voxels that were previously identified in the segmentation
process as belonging to the tumor 330. Moreover, the area outside the segmentation
boundary represents the voxels that were previously identified in the segmentation process as
not belonging to the tumor 330. Thus, the segmentation boundaries represent a line that
encapsulates the tumor 330.
Accordingly, and referring again to Figure 2, at 114 a segmentation
boundary is drawn around the object of interest. For example, as shown in Figure 5, the
viewport 350 includes a segmentation boundary 370 that encloses the tumor 330, the
viewport 352 includes a segmentation boundary 372 that encloses the tumor 330, and the
viewport 354 includes a segmentation boundary 374 that encloses the tumor 330. It should
be realized that the segmentation boundaries may be have different shapes depending on the
shape of the tumor 330 in each image plane being segmented. For example, as described
above, the tumor 330 shown in the 20 axial image 340 has a segmentation boundary 370
having a first shape. Whereas, the tumor 330 shown in the 20 sagittal image 342 and the 20
coronal image 344 have segmentation boundaries 372 and 374, respectively that have shapes
that are different than the segmentation boundary 370.
12
•
•
It should be realized that in the exemplary embodiment, the segmentation
boundary 370, for example, encapsulates substantially only the tumor 330. However, in
some embodiments, the segmentation boundary 370 may also include voxels that are not part
of the tumor 330 due to surrounding structures of similar image intensity as the tumor.
Accordingly, and as shown in Figure 6, in various embodiments the user may modify the size
of the bounding box 332, using for example, the icons 360 and 362 and repeat the
segmentation process to generate a revised set of segmented images displayed in the
respective viewer. For example, the user may resize the bounding box, as is described in
more detail below, in the segmented 20 axial image 300 to generate a revised segmented
axial image 301. In various embodiments, the image 300 may be displayed concurrently with
the revised image 301. Moreover, a visual indicator 380 may be displayed to indicate that the
bounding box 332 has been modified as described above.
Referring again to Figure 2, at 116 a second segmentation boundary on
another 20 plane of the volume of data defined inside the 3D bounding box is generated. More
specifically, in various embodiments, the shape of the tumor 330 and inclusion of non-tumor
voxels within the segmentation inside the bounding box may vary from slice to slice. For
example, as described above, the emission image dataset 34 is acquired along three
orthogonal axes to acquire an axial volume of emission information, a sagittal volume of
emission information, and a coronal volume of information. Moreover, each of the axial,
sagittal, and coronal volumes includes a plurality of slices. For example, the axial volume
includes a plurality of axial 20 images 310 (shown in Figure 4) of which the 20 axial image
300 (shown in Figure 5) represents one such image slice. Accordingly, in various
embodiments, a segmentation boundary is calculated for the tumor 330 in each of the slices
for each volume. More specifically, a segmentation boundary may be derived for each of the
axial 20 images 310, the sagittal 20 image 312, and the coronal 20 images 314.
However, in some instances, the tumor 330 may have a non-uniform shape.
For example, referring again to Figure 4, the tumor 330 may have a substantially round shape
in the 20 axial image 300 and a different shape in an 20 axial image 303. More specifically,
the shape of the tumor 330 may vary from slice to slice along the same viewing plane in the
same set of slices. However, as discussed above, it is often tedious and time consuming for a
user to manually review each image slice to determine the changes in the shape of the tumor.
13
Accordingly, at 118 the segmented 2D reference image is revised to include
a second segmentation boundary. For example, and referring to Figure 7, the 2D axial image
402 with segmentation boundary 384 may be revised as shown in image 404 to include a
second segmentation boundary 386 that is displayed concurrently with the first segmentation
boundary 384. In various embodiments, the second segmentation boundary 386 represents
the segmentation boundary derived from at least one of the slices forming the plurality of
slices taken along a single view. For example, in one embodiment, the second segmentation
boundary 386 may represent the segmentation boundary derived for the 2D axial image 303
(shown in Figure 4). The segmentation boundary derived for the 2D axial image 303 is then
superimposed onto the 2D axial image 300 such that the 2D axial image 300 displays the
• segmentation boundary 370 as derived from information acquired from the 2D axial image
303. In various other embodiments, the second segmentation boundary 376 may represent
the segmentation boundary derived for a plurality ofslices.
For example, and referring again to Figure 4 assume that the 2D axial image
300 is selected as a reference slice. The user then draws the bounding box 332 on the 2D
axial image 300 to perform a segmentation of the tumor 330. The 2D axial image is then
displayed including the segmentation boundary 370 of the tumor 330 as derived from the 2D
axial image 300. Moreover, the 2D axial image 300 also displays the second segmentation
boundary 376 that represents the combined segmentation boundaries derived from the
remaining images in the set of 2D axial images 310. In various embodiments, displaying a
respective 2D image that includes the segmentation boundary for the image and the
• segmentation boundaries for additional images enables a user to ascertain changes in the
shape of the tumor 330 without having to view additional slices. More, specifically, a user
can view a single image and determine whether the shape of the tumor is changing from
image to image along the same plane or if there are segmentation boundaries from other
image planes parallel to the reference image not connected to the current in-image tumor
border 370.
In various embodiments, the first segmentation boundary 370 may be
displayed using a first color and the second segmentation boundary 376 may be displayed
using a second different color. In other embodiments, the first segmentation boundary 370
may be displayed using a line having a first style, e.g. a solid line, and the second
14
•
•
segmentation boundary 376 may be displayed using a lin~ having a second style, e.g. a
dashed line.
Figure 7 is a plurality of images 400 that may be displayed in accordance
with various embodiments. In particular, maximum intensity pixel projection of the
segmented tumor borders is performed through each border in the set of 20 images to
generate the segmentation border shown in image 404. For example, the plurality of axial 20
images 310 may be utilized to form the MIP segmentation border 386. Moreover, the images
402 and 404 enable the user to perform various diagnostic tasks.
For example, in various embodiments, the ATLaS module 50 may be
activated by the user. In operation, the ATLaS module 50 is configured to generate and
display the various viewports and images described herein. Moreover, the ATLaS module 50
may also be configured to activate various icons and controls to enable the user to perform
various diagnostic tasks and/or to manipulate the bounding box 332, etc. as described above.
For example, the ATLaS module 50 may activate and display a visual indicator 382 that
enables the user to perform the segmentation. Such diagnostic tasks include, for example,
enabling the user to select various viewport configuration parameters and/or localize the
bounding box 332. Moreover, the ATLaS module 50 may enable a user to select a default
configuration wherein the voxels may be displayed or not displayed, the segmentation may be
shown or not shown, different slices, such as an upper and lower slice may be shown, a
continuation process may be activated to allow the segmentation to propagate outside the
bounding box 332, etc.
The ATLaS module 50 may also be configured to enable the user to display
a 30 image of the tumor 330. For example, Figure 8 shows an exemplary 20 axial image
450, a 20 sagittal image 452, and a 20 coronal image 454. In various embodiments, the
ATLaS module 50 may also automatically generate a viewport 460 and a viewport 462. In
various embodiments, the viewports 460 and 462 are utilized to display a portion of the at
least one of the images 450, 452, or 454. For example, in the illustrated embodiment, the
viewport 460 is configured to display a segmented image 470 of the axial image 450 that is
segmented as described above. Additionally, the ATLaS module 50 may enable the viewport
460 to enlarge or shrink the size of the image 470. For example, the viewport 460 may
15
•
•
include a type-in box 472 that the user may modify to resize the image 470. Additionally, the
viewport 460 may generate a 3D control box, that is some embodiments, may be a visual
representation of the bounding box 332 in three dimensions to enable the user to determine an
orientation, e.g. axial, sagittal, or coronal, of the segmented image 470. In various
embodiments, the control box 471 enables the user to rotate or reorient the displayed image
470. For example, the control box 471 may include a visual indicator 474 that identifies a
reference comer of the image 470. Thus, in operation, the visual indicator 474 is positioned
in the same position on the image 470 regardless of the orientation of the image 470.
Moreover, the control box 471 may include a plurality of control points 476
that enable the user to manipulate the size and/or orientation of the control box 471. In the
illustrated embodiment, the control points 476 are located at the comers of the control box
471. However, it should be realized that the control points 476 may be located anywhere on
the control box 471. Accordingly, when the control box 471 is operated in a 3D mode, the
user may manipulate the image 470 along all three axes by merely repositioning the control
box 471. In various embodiments, the viewport 462 may be utilized to display an image 480
acquired from a second modality such as the CT imaging system 12. In operation, the image
480 may be displayed concurrently with the image 470 to aid in localization of the tumor
330, for example.
A technical effect is to display a single 2D image that includes a
segmentation boundary drawn around an object of interest in the 2D image and a second
different segmentation boundary that is derived from segmentations of the object of interest
in other images generated along the same viewing plane. Accordingly, in operation, the
methods and systems described herein provide the user with an improved ability to perform
diagnosis while reducing the quantity of images viewed by the user to form the diagnosis.
Various embodiments of the methods and module 50, described herein may
be provided as part of, or used with, a medical imaging system, such as a dual-modality
imaging system 10 as shown in Figure 1. Figure 9 is a block schematic diagram of the
second modality unit 14, e.g. the PET imaging system, shown in Figure 1. As shown in
Figure 9, the PET system 14 includes a detector array 500 that is arranged as ring assembly of
individual detector modules 502. The detector array 10 also includes the central opening 22,
16
•
•
in which an object or patient, such as the subject 16 may be positioned, using, for 'example,
the motorized table 24 (shown in Figure 1). The motorized table 24 is aligned with the
central axis of the detector array 500. During operation, the motorized table 24 moves the
subject 16 into the central opening 22 of the detector array 500 in response to one or more
commands received from the operator workstation 30. More specifically, a PET scanner
controller 510 responds to the commands received from the operator workstation 30 through
the communication link 32. Therefore, the scanning operation is controlled from the operator
workstation 30 through PET scanner controller 510.
During operation, when a photon collides with a scintillator on the detector
array 500, the photon collision produces a scintilla on the scintillator. The scintillator
produces an analog signal that is transmitted to an electronics section (not shown) that may
form part of the detector array 500. The electronics section outputs an analog signal when a
scintillation event occurs. A set of acquisition circuits 520 is provided to receive these analog
signals. The acquisition circuits 520 process the analog signals to identify each valid event
and provide a set of digital numbers or values indicative of the identified event. For example,
this information indicates when the event took place and the position of the scintillation
scintillator that detected the event.
The digital signals are transmitted through a communication link, for
example, a cable, to a data acquisition controller 522. The data acquisition processor 522 is
adapted to perform the scatter correction and/or various other operations based on the
received signals. The PET system 12 may also include an image reconstruction processor
524 that is interconnected via a communication link 526 to the data acquisition controller
522. During operation, the image reconstruction processor 524 performs various image
enhancing techniques on the digital signals and generates an image ofthe subject 16.
As used herein, a set of instructions may include various commands that
instruct the computer or processor as a processing machine to perform specific operations
such as the methods and processes of the various embodiments of the invention. The set of
instructions may be in the form of a software program, which may form part of a tangible
non-transitory computer readable medium or media. The software may be in various forms
such as system software or application software. Further, the software may be in the form of
17
•
•
a collection of separate programs or modules, a program module within a larger program or a
portion of a program module. The software also may include modular programming in the
form of object-oriented programming. The processing of input data by the processing
machine may be in response to operator commands, or in response to results of previous
processing, or in response to a request made by another processing machine.
As used herein, the terms "software" and "firmware" may include any
computer program stored in memory for execution by a computer, including RAM memory,
ROM memory, EPROM memory, EEPROM memory, and non-volatile RAM (NVRAM)
memory. The above memory types are exemplary only, and are thus not limiting as to the
types ofmemory usable for storage of a computer program.
It is to be understood that the above description is intended to be illustrative,
and not restrictive. For example, the above-described embodiments (and/or aspects thereof)
may be used in combination with each other. In addition, many modifications may be made
to adapt a particular situation or material to the teachings of the various embodiments without
departing from their scope. While the dimensions and types of materials described herein are
intended to defme the parameters of the various embodiments, they are by no means limiting
and are merely exemplary. Many other embodiments will be apparent to those of skill in the
art upon reviewing the above description. The scope of the various embodiments should,
therefore, be determined with reference to the appended claims, along with the full scope of
equivalents to which such claims are entitled. In the appended claims, the terms "including"
and "in which" are used as the plain-English equivalents ofthe respective terms "comprising"
and "wherein." Moreover, in the following claims, the terms "first," "second," and "third,"
etc. are used merely as labels, and are not intended to impose numerical requirements on their
objects. Further, the limitations of the following claims are not written in means-plusfunction
format and are not intended to be interpreted based on 35 u.S.C. § 112, sixth
paragraph, unless and until such claim limitations expressly use the phrase "means for"
followed by a statement of function void of further structure.
This written description uses examples to disclose the various embodiments,
including the best mode, and also to enable any person skilled in the art to practice the
various embodiments, including making and using any devices or systems and performing
18
,.
any incorporated methods. The patentable scope of the various embodiments is defmed by
the claims, and may include other examples that occur to those skilled in the art. Such other
examples are intended to be within the scope of the claims if the examples have structural
elements that do not differ from the literal language of the claims, or the examples include
equivalent structural elements with insubstantial differences from the literal languages of the
claims.
19
Docket Number
Parts List
Imaging system 10
First modality unit 12
Second modality unit 14
Subject 16
Gantry 18
Gantry 20
Central opening 22
Motorized table 24
X-ray source 26
Detector 28
Worlcstation 30
Attenuation projection data set 32
Emission projection dataset 34
Communication link 36
Computer 40
Display 42
Input device 44
ATLaS module 50
Method 100
At 102
At 104
At 106
At 108
At 110
At 112
At 114
Plurality of slices 200
First slice 202
Second slice 204
Third slice 206
nth slice 208
Docket Number
2D axial image 300
Revised segmented image 301
2D sagittal image '" 302
2D axial image 303
2D coronal image 304
2D axial images 31 0
Sagittal 20 image 312
Coronal 20 images 314
Tumor 330
Bounding box 332
2D segmented axial image 340
2D segmented sagittal image 342
2D segmented coronal image 344
Viewport 350
Viewport 352
Icons 360
Icons 362
Segmentation boundary 370
Segmentation boundary 372
Segmentation boundary 374
Second Segmentation boundary 376
Visual indicator 380
Visual indicator 382
Plurality of images 400
MIP image 402
MIP image 404
Detector array 500
Detector modules 502
PET scanner controller 510
Acquisition circuits 520
Data acquisition processor 522
Image reconstruction processor 524
Communication link 526

•
•
We Claims:
1. A method for displaying a segmented two-dimensional (2D) image, the
method comprising:
obtaining a three-dimensional (3D) volume dataset corresponding to an imaged
volume along a viewing plane;
segmenting an object of interest within 3D volume to generate a plurality of
segmented two-dimensional (2D) images along the viewing plane;
selecting a reference image for viewing from the plurality of segmented 2D images;
and
displaying the reference image, the reference image having a fIrst segmentation
boundary drawn around the object of interest and a second segmentation boundary drawn
around the object of interest, the fIrst segmentation boundary being derived from the
segmentation performed on the reference image and the second segmentation boundary being
derived from the segmentation performed on at least one non-reference image of the plurality
of segmented 2D images.
2. The method of Claim 1, wherein the second segmentation boundary comprises
a composite segmentation boundary derived from a plurality of non-reference images
generated along the viewing plane.
3. The method of Claim 1, wherein the fIrst segmentation boundary has a fIrst
color and the second segmentation boundary has a second different color.
4. The method of Claim 1, wherein the fIrst segmentation boundary has a fIrst
style and the second segmentation boundary has a second different style.
5. The method of Claim 1, further comprising positioning a bounding box around
the object of interest to perform the segmentation.
6. The method of Claim 5, further comprising:
•
•
modifying a size of the bounding box; and
generating a revised segmented image based on the modified bounding box.
7. The method of Claim 1, further comprising:
defining a seed point in the object of interest;
generating a bounding box around the object of interest based on the seed point; and
generating a revised segmented image based on the modified bounding box.
8. The method of Claim 1, wherein the 3D volume dataset comprises a 3D
emission image dataset.
9. A system for displaying a segmented two-dimensional (2D) image, the system
comprising:
a medical imaging scanner; and
a computer coupled to the medical imaging scanner, the computer configured to
obtain a three-dimensional (3D) volume dataset corresponding to an imaged
volume along a viewing plane from the medical imaging scanner;
segment an object of interest within 3D volume to generate a plurality of
segmented two-dimensional (2D) images along the viewing plane;
receive an input selecting a reference image for viewing from the plurality of
segmented 2D images; and
automatically display the reference image, the reference image having a first
segmentation boundary drawn around the object of interest and a second segmentation
boundary drawn around the object of interest, the first segmentation boundary being
derived from the segmentation performed on the reference image and the second
segmentation boundary being derived from the segmentation performed on at least
one non-reference image of the plurality of segmented 2D images.
•
10. The system of Claim 10, wherein the second segmentation boundary
comprises a composite segmentation boundary derived from a plurality of non-reference
images generated along the viewing plane.
11. The system of Claim 10, wherein the fIrst segmentation boundary has a fIrst
color and the second segmentation boundary has a second different color.
12. The system of Claim 10, wherein the fIrst segmentation boundary has a fIrst
style and the second segmentation boundary has a second different style.
13. The system of Claim 10, wherein the computer is further confIgured to receive
an input to position a bounding box around the object of interest to perform the segmentation.
14. The system of Claim 10, wherein the computer is further confIgured to:
receive an input to modify a size of the bounding box; and
automatically generate a revised segmented image based on the modifIed bounding
box.
15. The system of Claim 10, wherein the medical imaging scanner comprises a
positron emission tomography (PET) system.
16. A non-transitory computer readable medium encoded with a program
prograIli111ed to instruct a computer to:
• obtain a three-dimensional (3D) volume dataset corresponding to an imaged volume
along a viewing plane from the medical imaging scanner;
segment an object of interest within 3D volume to generate a plurality of segmented
two-dimensional (2D) images along the viewing plane;
receive an input selecting a reference image for viewing from the plurality of
segmented 2D images; and
automatically display the reference image, the reference image having a fIrst
segmentation boundary drawn around the object of interest and a second segmentation
2J.,
boundary drawn around the object of interest, the first segmentation boundary being derived
from the segmentation performed on the reference image and the second segmentation
boundary being derived from the segmentation performed on at least one non-reference
image of the plurality of segmented 2D images.
17. The non-transitory computer readable medium of Claim 16, wherein the
second segmentation boundary comprises a composite segmentation boundary derived from a
plurality of non-reference images generated along the viewing plane.
18. The non-transitory computer readable medium of Claim 16, wherein the first
segmentation boundary has a first color and the second segmentation boundary has a second
• different color.
19. The non-transitory computer readable medium of Claim 16, wherein the first
segmentation boundary has a first style and the second segmentation boundary has a second
different style.
20. The non-transitory computer readable medium of Claim 16, wherein the
program is further programmed to instruct the computer to:
receive an input to modify a size of the bounding box; and
automatically generate a revised segmented image based on the modified bounding
box.