Description:TECHNICAL FIELD
The present disclosure relates to system for the characterization of biological tissues. More specifically, the present disclosure relates to a portable optical system for real-time characterization of biological tissues.
BACKGROUND
Tissue characterization is an essential component of medical diagnostics and surgical planning. Disorders such as fibrosis, cancer, and inflammation significantly impact biological tissues, altering their structural and functional properties. Fibrosis, a common pathological process, involves the excessive accumulation of extracellular matrix proteins such as collagen and affects vital organs such as the heart, lungs, liver, and kidneys. Fibrosis leads to tissue stiffening, functional impairment, and, in advanced cases, organ failure. The early and accurate identification of fibrotic and other pathological changes in biological tissues is critical for timely intervention and improved patient outcomes.
Current diagnostic techniques primarily include invasive biopsies and imaging modalities. While biopsies remain the gold standard for detecting structural changes like collagen deposition, they are invasive, pose risks, and have limitations, such as sampling errors and logistical challenges. Non-invasive imaging techniques, such as computed tomography (CT), cardiac magnetic resonance imaging (CMRI), and echocardiography, offer advantages in visualizing organ-wide abnormalities. However, the existing methods often lack the resolution or specificity needed for detailed tissue characterization and rely on external contrast agents or ionizing radiation, introducing additional limitations.
Efforts to characterize biological tissues intraoperatively have explored optical methods, but existing systems are hindered by low sensitivity, complex operational requirements, and the inability to quantify specific tissue properties in real time. The limitations highlight the gap in current technologies for accurately distinguishing healthy from pathological tissues during surgical and diagnostic procedures.
Therefore, considering the foregoing discussion, there exists a need to overcome the aforementioned drawbacks.
SUMMARY
The present disclosure provides a portable optical system for the characterization of a biological tissue. The present disclosure provides a solution to the technical problem of how to accurately characterize biological tissues, particularly distinguishing between healthy and pathological tissues such as fibrotic, cancerous, or inflamed tissues. An aim of the present disclosure is to provide a solution that overcomes at least partially the problems encountered in the prior art and provides an improved portable optical system for the characterization of the biological tissue. The portable optical system integrates polarization-based optical spectroscopy with advanced processing capabilities to deliver precise quantification of tissue properties. By incorporating features such as adjustable polarization states, an optical fiber-based probe, and real-time analysis, the portable optical system facilitates detailed tissue characterization without the need for contrast agents or invasive procedures. Furthermore, the compact design of the portable optical system and user-friendly graphical interface make it suitable for clinical use, aiding surgeons and clinicians in accurate diagnosis and effective surgical decision-making.
One or more objectives of the present disclosure is achieved by the solutions provided in the enclosed independent claims. Advantageous implementations of the present disclosure are further defined in the dependent claims.
In one aspect, the present disclosure provides a portable optical system for characterization of biological tissue, comprising: a portable optical system for characterization of biological tissue, comprising:
a polarization-based optical device comprising:
a transmission module configured to automatically generate and direct a transmitted light at a plurality of predetermined angles onto a biological tissue;
a reception module configured to automatically receive and analyze light reflected from the biological tissue;
an optical fiber-based probe operatively connected to the transmission module and the reception module, and configured to direct the transmitted light onto the biological tissue and collect the reflected light from the biological tissue; and
at least one motor configured to automatically adjust polarization states to a plurality of predetermined angles; and
a processor operatively connected to the transmission module, the reception module, the optical probe, and the at least one motor of the polarization-based optical device, the processor configured to:
control the at least one motor to automatically adjust the polarization states to the plurality of predetermined angles;
receive, from the reception module, a plurality of light intensity measurements corresponding to different combinations of the polarization states;
calculate values for a plurality of predefined optical parameters based on the received light intensity measurements at the different polarization states and display the calculated values on a graphical user interface (GUI);
characterize the biological tissue based on the calculated values of the plurality of predefined optical parameters; and
generate an output indicating characterization of the biological tissue on the GUI.
The portable optical system analyzes the interaction of the polarized light with biological tissues with real-time analysis capability. This enables rapid and precise differentiation between healthy and pathological tissues, aiding in immediate clinical decision-making during surgical and diagnostic procedures. The integration of at least one motor to adjust polarization states of light to a plurality of predetermined angles enhances the sensitivity of the portable optical system. The adjustment allows for detailed analysis of tissue optical properties by capturing diverse polarization signatures, providing more comprehensive insights into the biological tissue composition and abnormalities. The compact and portable nature of the portable optical system allows it to be easily transported and deployed in various clinical settings, including operating rooms and remote locations. The user-friendly graphical interface ensures that the portable optical system can be operated with minimal training, increasing its usability among medical professionals. The portable optical system is capable of characterizing a wide range of tissue types, including fibrotic, cancerous, solid tumors, and inflamed tissues. The versatility of the portable optical system extends its applications across various organs, such as the heart, liver, lungs, and kidneys, and enables its use in diverse medical scenarios like intraoperative guidance and disease monitoring. By providing immediate feedback on the properties of the biological tissues, the portable optical system facilitates real-time surgical guidance. Surgeons can accurately differentiate between healthy and diseased tissue during procedures, minimizing unnecessary tissue removal and improving surgical precision. The precise measurement of optical parameters reduces the potential for diagnostic errors associated with sampling bias in biopsies or low specificity in imaging modalities. The precise measurements lead to more reliable diagnoses and better patient outcomes. Unlike imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), which often require external contrast agents, the portable optical system operates label-free. The label-free nature of the portable optical system reduces patient exposure to potentially harmful substances and simplifies the diagnostic process. The portable optical system can incorporate trained machine learning models to further enhance its diagnostic capabilities. By comparing obtained optical parameters with training datasets, the portable optical system can classify tissues as healthy or pathological with greater accuracy, continuously improving through learning. The energy-efficient components of the portable optical device, such as the light source and motors, contribute to its overall cost-effectiveness of the portable optical system. The ability of the portable optical system to provide detailed tissue characterization without the need for expensive consumables or complex imaging systems further reduces operational costs. The modular design of the portable optical system allows for future enhancements, such as integrating additional sensors or expanding its application to other medical or non-medical tissue analysis scenarios.
In another aspect, the present disclosure provides a method for characterizing biological tissue using the portable optical system, the method comprising:
generating and directing, by a transmission module and an optical fiber-based probe, polarized light at a plurality of predetermined angles onto a biological tissue;
collecting, by the optical fiber-based probe, light reflected from the biological tissue;
receiving and analyzing, by a reception module, the reflected light from biological tissue;
adjusting, by at least one motor, polarization states of the reflected light to the plurality of predetermined angles;
receiving, by a processor, a plurality of light intensity measurements from the reception module corresponding to different combinations of the polarization states of the reflected light from the biological tissue;
calculating, by the processor, values for a plurality of predefined optical parameters based on the received light intensity measurements at the different polarization states of the reflected light;
characterizing, by the processor, the biological tissue based on the calculated values of the plurality of predefined optical parameters;
generating, by the processor, an output indicating characterization of the biological tissue based on the calculated values of the plurality of predefined optical parameters; and
displaying, by the processor, the received light intensity measurements of the reflected light and the calculated values of the plurality of predefined optical parameters for the biological tissue on the GUI.
The method for characterizing biological tissue using the portable optical system of the present disclosure has same technical effects as described above for portable optical system.
It is to be appreciated that all the aforementioned implementation forms can be combined. All steps which are performed by the various entities described in the present application as well as the functionalities described to be performed by the various entities are intended to mean that the respective entity is adapted to or configured to perform the respective steps and functionalities. It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.
Additional aspects, advantages, features, and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative implementations construed in conjunction with the appended claims that follow.
BRIEF DESCRIPTION OF THE DRAWINGS
The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those skilled in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.
Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:
FIG. 1 is a block diagram of a portable optical system for characterization of a biological tissue, in accordance with an embodiment of the present disclosure;
FIG. 2A is a diagram illustrating a schematic of a polarisation-based optical system for characterization of the biological tissue, in accordance with an embodiment of the present disclosure;
FIG. 2B is a diagram illustrating an exploded view of the polarisation-based optical system for characterization of the biological tissue, in accordance with an embodiment of the present disclosure; and
FIG. 3 is a flowchart for a method for characterizing biological tissue using the portable optical system, in accordance with an embodiment of the present disclosure.
In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.
DETAILED DESCRIPTION OF EMBODIMENTS
The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practicing the present disclosure are also possible.
FIG. 1 is a block diagram of a portable optical system for characterization of a biological tissue, in accordance with an embodiment of the present disclosure. With reference to FIG.1, there is shown a block diagram that includes a portable optical system 100 (hereinafter referred to as the optical system 100). The optical system 100 includes a polarization-based optical device 102 (hereinafter referred to as the optical device 102), a processor 106 and a memory 108. In an implementation, the optical system 100 further includes a trained machine learning model 110. The processor 106 is communicatively coupled with the memory 108 and the trained machine learning model 110. The optical system 100 may be used for characterizing biological tissues through polarization-based measurements, with a particular focus on differentiating between healthy and fibrotic tissues. Specifically, the optical system 100 enables real-time tissue analysis and provides critical guidance during surgical procedures. By utilizing polarized light interactions with biological tissues, the optical system 100 calculates optical parameters that indicate the health status of the biological tissue. The optical system 100 finds application in various medical scenarios, including cardiac tissue characterization during heart surgeries, liver tissue assessment for fibrosis, and kidney tissue evaluation. Additionally, optical system 100 is well-suited for detecting cancer tissue margins, identifying inflammatory tissues and solid tumors, offering real-time surgical guidance, and performing tissue assessments.
In an implementation, the processor 106, the memory 108, and the trained machine learning model 110 may be implemented on the same server, such as a server 104. In some implementations, the optical system 100 further includes a storage device 114. In some implementations, the storage device 114 is configured to store a training dataset 116. In some implementations, the training dataset 116 may be stored in the same server, such as the server 104.
In some implementations, the storage device 114 is communicatively coupled to the server 104 via a communication network 112. The server 104 may be communicatively coupled to a plurality of user display devices, such as a user display device 118, via the communication network 112. The user display device 118 includes a graphical user interface (GUI) 120. The user display device 118 may be configured to receive calculated values for a plurality of predefined optical parameters.
The optical device 102 is a polarization-based compact instrument for real-time biological tissue characterization using polarized light. The optical device 102 measures tissue-light interactions across different polarization states by analyzing the measured optical parameters which aids to differentiate healthy from fibrotic tissues.
The server 104 includes suitable logic, circuitry, interfaces, and code that may be configured to communicate with the user display device 118 via the communication network 112. In an implementation, the server 104 may be a master server or a master machine that is a part of a data center that controls an array of other cloud servers communicatively coupled to it for load balancing, running customized applications, and efficient data management. Examples of the server 104 may include, but are not limited to a cloud server, an application server, a data server, or an electronic data processing device.
The processor 106 refers to a computational element that is operable to respond to and processes instructions that drive the optical system 100. The processor 106 may refer to one or more individual processors, processing devices, and various elements associated with a processing device that may be shared by other processing devices. Additionally, the one or more individual processors, processing devices, and elements are arranged in various architectures for responding to and processing the instructions that drive the optical system 100. In some implementations, the processor 106 may be an independent unit and may be located outside the server 104 of the optical system 100. Examples of the processor 106 may include but are not limited to, a hardware processor, a digital signal processor (DSP), a microprocessor, a microcontroller, a complex instruction set computing (CISC) processor, an application-specific integrated circuit (ASIC) processor, a reduced instruction set (RISC) processor, a very long instruction word (VLIW) processor, a state machine, a data processing unit, a graphics processing unit (GPU), and other processors or control circuitry.
The memory 108 refers to a volatile or persistent medium, such as an electrical circuit, magnetic disk, virtual memory, or optical disk, in which a computer may store data or software for any duration. Optionally, the memory 108 is a non-volatile mass storage, such as a physical storage media. Examples of implementation of the memory 108 may include, but are not limited to, an Electrically Erasable Programmable Read-Only Memory (EEPROM), Dynamic Random-Access Memory (DRAM), Random Access Memory (RAM), Read-Only Memory (ROM), Hard Disk Drive (HDD), Flash memory, a Secure Digital (SD) card, Solid-State Drive (SSD), and/or CPU cache memory.
The trained machine learning model 110 refers to a software component or an integrated circuitry comprising an artificial intelligence (AI) engine that incorporates an artificial intelligence model, designed to characterize biological tissues based on optical parameters. The trained machine learning model 110 is trained using a comprehensive dataset containing ranges of predefined optical parameters including normalized anisotropy, anisotropy degree, depolarization coefficient, linear polarizance, linear diattenuation, orientation of maximum transmittance for linear polarizance, and orientation of maximum transmittance for linear diattenuation collected from tissue samples. The optical parameters are derived from light intensity measurements taken at different polarization states when light interacts with both healthy and diseased tissue samples. The trained machine learning model 110 processes optical parameter measurements in real-time, comparing them against its trained dataset to classify the tissue as either healthy or diseased.
The communication network 112 includes a medium (e.g., a communication channel) through which the user display device 118 communicates with the server 104. The communication network 112 may be a wired or wireless communication network. Examples of the communication network 112 may include, but are not limited to, a Local Area Network (LAN), a wireless personal area network (WPAN), a Wireless Local Area Network (WLAN), a wireless wide area network (WWAN), a cloud network, a Long-Term Evolution (LTE) network, a plain old telephone service (POTS), a Metropolitan Area Network (MAN), and/or the Internet.
The storage device 114 may be any storage device that stores data and applications without any limitation thereto. In an implementation, the storage device 114 may be a cloud storage or an array of storage devices.
The training dataset 116 refers to a comprehensive collection of predefined optical parameter values obtained from the biological tissue samples that have been validated by medical experts. In an implementation, the training dataset 116 includes ranges of the values of the plurality of predefined optical parameters for healthy tissue samples identified by medical experts and ranges of the values of the plurality of predefined optical parameters for diseased tissue samples identified by the medical experts. For each tissue type, the training dataset 116 contains precise measurements of light intensity values at different polarization states and their corresponding tissue classifications. The optical parameters serve as reference values for the trained machine learning model 110 to accurately classify unknown tissue samples during real-time characterization.
The user display device 118 refers to an electronic computing device operated by medical professionals to interact with the optical system 100. In some implementations, the user display device 118 may be configured to display real-time tissue characterization results and optical parameter measurements through the GUI 120. Examples of the user display device 118 may include, but are not limited to, medical display monitors, surgical navigation systems, operating room displays, mobile medical tablets, medical-grade computers, or other compatible medical display devices that can be used in clinical settings. The user display device 118 enables medical professionals to visualize and interpret characterization results of the biological tissue during surgical procedures, facilitating informed decision-making based on real-time tissue analysis.
The GUI 120 refers to an interactive interface displayed on the user display device 118 that presents real-time tissue characterization data in an intuitive visual format. In an example, the GUI 120 may include a dynamic dashboard featuring Mueller matrix elements, optical parameters, and tissue classification results. The GUI 120 may also include numerical displays showing measured intensities at different polarization states, graphical representations of optical parameters through gauges and charts, and a clear classification output providing immediate feedback during surgical procedures.
FIG. 2A is a diagram illustrating a schematic of a portable optical device for characterisation of the biological tissue, in accordance with an embodiment of the present disclosure. FIG. 2A is explained in conjunction with elements from FIG.1. With reference to FIG. 2A, there is shown the optical device 102, including a transmission module 202, a reception module 204, and an optical fiber-based probe 206. The transmission module 202 includes a light source 208 configured to emit light at a predetermined wavelength, a first collimator 210 configured to collimate the emitted light, a first linear polarizer 212 and a second collimator 214.
The reception module 204 includes a reception collimator 216 configured to collimate the reflected light, a second linear polarizer 218 configured to polarize the reflected light collimated by the reception collimator 216, and a photodetector 220 configured to measure the intensity of a polarized reflected light from the biological tissue. The optical fiber-based probe 206 includes a transmission fiber 222A configured to direct the polarized transmitted light onto the biological tissue 226; and a reception fiber 222B configured to collect the reflected light from the biological tissue.
The transmission module 202 refers to a section of the optical device 102 responsible for generating and directing polarized light onto a target biological tissue. The transmission module 202 includes a plurality of elements like a light source, collimators, and polarizers to ensure the light is appropriately conditioned for interaction with the target material or biological tissue.
The reception module 204 refers to component of the optical device 102 responsible for collecting and analysing light reflected from the biological tissue. A probe tip 224 of the optical fiber-based probe 206 transmits polarized light onto the biological tissue 226 and transmits reflected light from the biological tissue 226 to the reception module 204.
The light source 208 refers to the component within the transmission module 202 responsible for emitting light at a specific wavelength for characterization of the biological tissue. In some examples, the light source 208 may include a laser diode for coherent and precise light emission, a light-emitting diode (LED) for broader spectral output, or a tunable laser for adjustable wavelength ranges to suit specific diagnostic need.
The first collimator 210 refers to an optical component within the transmission module 202 that shapes and aligns the emitted light from the light source 208 into a parallel beam, which ensures consistent light propagation, improving the precision and accuracy of its interaction with biological tissue.
The first linear polarizer 212 refers to the component within the transmission module 202 that linearly polarizes the collimated light beam emitted by the light source 208. The first linear polarizer 212 ensures the light has a specific polarization state, enabling precise interaction with the biological tissue and enhancing the accuracy of tissue characterization by analysing polarization-dependent optical properties.
The second collimator 214 refers to an optical component within the transmission module 202 designed to focus the polarized light emerging from the first linear polarizer 212 onto the transmission fiber 222A of the optical fiber-based probe 206. In an implementation, the second collimator 214 may include a high-precision lens or lens assembly engineered to minimize optical aberrations and maintain beam uniformity. The second collimator 214 ensures that the polarized light is tightly focused with minimal divergence, facilitating efficient coupling into the transmission fiber 222A of the optical fiber-based probe 206 while preserving the polarization state. The specifications of the second collimator 214, such as numerical aperture (NA), focal length, and anti-reflective coating, are optimized for the specific wavelength of the light source used in the optical system 100, ensuring high optical efficiency and minimal energy loss.
The reception collimator 216 refers to a fiber collimator within the reception module 204 that collects the reflected light from the biological tissue via reception fiber 222B and converts it into a parallel beam. As a fiber collimator, the reception collimator 216 comprises an optical fiber aligned with a precision lens system to ensure efficient coupling of reflected light while preserving its polarization state and optical quality.
The second linear polarizer 218 refers to a component within the reception module 204 that polarizes the collimated light collected by the reception collimator 216. The second linear polarizer 218 selectively transmits light with a specific polarization state, allowing the optical system 100 to analyze changes in polarization caused by the interaction of light with the biological tissue, which is crucial for accurate tissue characterization.
The photodetector 220 refers to a component within the reception module 204 designed to measure the intensity of the polarized light after it passes through the second linear polarizer 218. The photodetector 220 converts the optical signal into an electrical signal, enabling the optical system 100 to analyze the light's interaction with the biological tissue.
FIG. 2B is a diagram illustrating an exploded view of the optical device for characterization of the biological tissue, in accordance with an embodiment of the present disclosure. FIG. 2B is explained in conjunction with elements from FIGs.1 and 2A. With reference to FIG. 2B, there is shown an exploded view of the optical device 102. The optical device 102 features the transmission module 202 and the reception module 204, housed within an outer casing 246 with a top lid 252. The transmission module 202, the light source 208, the first collimator 210, the first linear polarizer 212 mounted in a geared polarizer holder 228. The reception module 204 includes the second linear polarizer 218, the photodetector 220 holded by a photodetector holder 240 followed by the reception collimator 216. The reception collimator 216 is holded by a collimator holder 234. The optical device 102 further includes at least one motor (as illustrated in embodiment of FIG.2B, a first motor 230 having a first bevel gear 232 and a second motor 236 having a second bevel gear 238). The first linear polarizer 212 is controlled by the first motor 230 coupled with the first bevel gear 232. Similarly, the second linear polarizer 218 is controlled by the second motor 236 coupled with the second bevel gear 238. The optical device 102 incorporates polymer bearings for smooth mechanical movement and specialized holders for securing the optical components. The optical device 102 further incorporates the electronic components including a main PCB 248, a LED display 242, and a control switch 244 mounted within the outer casing 246. Further, the optical device 102 includes a front cover 250.
Referring to FIGs. 1, 2A and 2B, in operation, the light source 208 (for example, laser diode) in transmission module 202 generates light at a predetermined wavelength (for example, 1550 nm). The emitted light from the light source 208 is initially unpolarized. The emitted light enters the first collimator 210 and the first collimator 210 converts divergent emitted light into parallel beam. The collimated emitted light ensures uniform light intensity across the beam cross-section and reduces light loss in subsequent optical components of the transmission module 202. Further, the collimated emitted light passes through the first linear polarizer 212. The first linear polarizer 212 is mounted in the geared polarizer holder 228 and connected to the first motor 230. In an implementation, the processor 106 of the main PCB 248 is configured to control the first motor 230 to adjust the polarization states to the plurality of predetermined angles. The first motor 230 rotates the first linear polarizer 212 to specific angles (e.g., 0 degrees, 45 degrees, 90 degrees, 135 degrees) relative to the incoming light beam. The specific angles determine the orientation of the polarization axis. As the first motor 230 rotates the first linear polarizer 212 to predetermined angles, the first linear polarizer 212 selectively filters the light waves. Only the light waves aligned with the axis of the first linear polarizer 212 at the current angle are transmitted, while others are blocked. The alignment creates a controlled and well-defined polarization state at each angle. The precise control of the first motor 230 ensures that the first linear polarizer 212 can be rotated to exact angles repeatedly, maintaining consistent polarization states. Further, the polarized collimated emitted light enters the second collimator 214. The second collimator 214 focuses the polarized collimated emitted light as a transmitted light for efficient coupling. The transmitted light is directed into a transmission fiber 222A, which ensures maximum light coupling efficiency. The transmitted light enters the transmission fiber 222A. The transmission fiber 222A guides the transmitted light to the probe tip 224 which touches the biological tissue 226 during measurement. The transmitted light exits the transmission fiber 222A and illuminates the biological tissue 226.
Once the light is reflected from the biological tissue 226 the reception module 204 receives reflected light from the biological tissue 226 via the reception fiber 222B. The reflected light contains modified polarization states due to interaction with the biological tissue 226. The intensity and polarization state of the reflected light carry information of the biological tissue 226. The reception collimator 216 receives light from the reception fiber 222B. The reception collimator 216 converts divergent light from the reception fiber 222B into parallel beam. The reception collimator 216 ensures uniform light distribution for accurate analysis and maintains polarization state during collimation. The reflected collimated light passes through the second linear polarizer 218. The processor 106 of the main PCB 248 sends control signals to the second motor 236, dictating the exact angle to which the second linear polarizer 218 should be rotated. The processor 106 ensures that the rotation of the second linear polarizer 218 aligns with the timing of the optical measurements. Once the second motor 236 positions the second linear polarizer 218 at the desired angle, the processor 106 triggers the reception module 204 to capture the light intensity for that specific polarization state. The processor 106 can dynamically adjust the angles of the second linear polarizer 218 during real-time operation. The processor 106 monitors the position of the second motor 236 using feedback from the motor controller to ensure that the second linear polarizer 218 is accurately aligned to the intended angle. If any deviation is detected, the processor 106 can issue corrective commands to maintain precision. For each polarization angle, the processor 106 receives and stores the measured light intensity from the reception module 204. By comparing the data across different angles, the processor 106 calculates polarization-dependent optical parameters, such as anisotropy degrees, depolarization coefficient etc. Further, the photodetector 220 receives the polarized reflected light and measures light intensity at each polarization state, converts optical signals to electrical signals and provides a precise plurality of intensity measurements.
Further, the processor 106 is configured to receive from the reception module 204 a plurality of light intensity measurements corresponding to different combinations of the polarization states. The electrical signals representing light intensity are transmitted from the reception module 204 to the processor 106 through an electronic interface. The electronic signals are organized into a data set, where each measurement corresponds to a specific combination of the incident and reflected polarization states. The processor 106 receives the plurality of light intensity readings in quick succession, corresponding to different polarization state combinations. The processor 106 maps each intensity measurement to its associated polarization state combination for structured analysis. Any noise or inconsistencies in the measurements are addressed using filtering algorithms or calibration data. The processor 106 organizes the received data into arrays or matrices (for example, Mueller matrix), preparing it for the calculation of optical parameters from the matrix elements. The measurements serve as the foundation for subsequent tissue characterization, as they provide insights into how the biological tissue interacts with polarized light.
Further, the photodetector 220 measures the intensity of the reflected light at different combinations of incident and reflected polarization states (e.g. 0 degrees, 45 degrees, 90 degrees, 135 degrees).
The Mueller matrix represents how the biological tissue modifies the light’s polarization.
For example, for a 3x3 Mueller matrix in this example.
M=[■(m_11&m_12&m_13@m_21&m_22&m_23@m_31&m_32&m_33 )]
Elements of Mueller matrix “M” are calculated using intensity measurements and known formulae:
Let m11=0.7, m12=0.1, and m13=0.1
Using the Mueller matrix elements, optical parameters may be derived, for example, linear diattenuation (LD) is given by:
(LD)= sqrt {(m12)2 +(m13)2} =sqrt {(0.1)2+(0.1)2} =sqrt {0.02}=0.14
Similarly, different optical parameters may be calculated using the respective formulae.
Normalized Anisotropy (A)= (2*(m_22+m_33 )*sqrt[( m_(22 )+ m_33 )^2+(m_23+m_32 )^2 ])/((m_22+m_33 )^2+(m_22-m_33 )^2+(m_23+m_32 )^2 )
Depolarization coefficient (b) = (m_22+m_33)/2
Linear Polarizance (LP)= sqrt((m_21 )^2+(m_31 )^2 )
Orientation of maximum transmittance for Linear Polarizance
Anisotropy Degrees,
t_1=sqrt[(m_22-m_33 )^2+(m_23+m_32 )^2 ]/2
t_2=sqrt[(m_21 )^2+(m_31 )^2 ]/2
Orientation of maximum transmittance for Linear Diattenuation (α_(D ))

Linear Diattenuation (LD)= sqrt((m_12 )^2+(m_13 )^2 )
In an implementation, the processor 106 is configured to display the calculated values for a plurality of predefined optical parameters through the GUI 120. The processor 106 characterize the biological tissue based on the calculated values of the optical parameters. In an implementation, the trained machine learning model 110 is configured to receive the obtained optical parameters as input. The trained machine learning model 110 checks the incoming data for completeness and correctness, ensuring no optical parameters are missing or out of range. If required, the trained machine learning model 110 preprocesses the data, which may include scaling the optical parameters to a standard range (e.g., 0 to 1) to match the training dataset of the trained machine learning model 110.
The preprocessed optical parameters are fed into the input layer of the trained machine learning model 110. The trained machine learning model 110, having been trained on similar data formats, processes the optical parameters seamlessly. The trained learning model 110 compares the received optical parameters with the training dataset 116. In an implementation, the training dataset 116 includes ranges of the values of the plurality of predefined optical parameters for healthy tissue samples identified experimentally and ranges of the values of the plurality of predefined optical parameters for fibrotic tissue samples identified experimentally.
For healthy tissue samples, if for example medical experts have identified specific ranges for normalized anisotropy (0.85-0.95), depolarization coefficient (4.0-5.0), linear polarizance (4.0-5.0), and linear diattenuation (20-25). Similarly, for fibrotic tissue samples, medical experts have established different characteristic ranges: normalized anisotropy (0.4-0.7), depolarization coefficient (2.0-3.5), linear polarizance (2.0-3.5), and linear diattenuation (10-15). When new measurements are taken, the trained machine learning model 110 compares the received optical parameters against these expert-validated ranges. For example, if a tissue sample shows a normalized anisotropy of 0.89, depolarization coefficient of 4.98, linear polarizance of 4.5, and linear diattenuation of 24.67, the trained machine learning model 110 compares these values with both healthy and fibrotic ranges. The close alignment of the optical parameters with the healthy tissue ranges would lead to a classification of the sample as healthy tissue with a high confidence score.
FIG. 3 is flowchart method for characterizing biological tissue using the portable optical system, in accordance with an embodiment of the present disclosure. FIG. 3 is explained in conjunction with elements from FIGs. 1 to 2B. In some implementations, the method 300 is executed by a skilled person. The method 300 may include steps 302 to 318.
At step 302, the method 300 includes generating and directing, by the transmission module 202 and the optical fiber-based probe 206, polarized light at a plurality of predetermined angles onto the biological tissue 226. The predetermined angles are specifically chosen for optimal tissue penetration and interaction. As the light emerges from the laser diode, it is initially divergent, spreading out in a cone-like pattern. The divergent light then enters the first collimator 210, which utilizes precision optics to transform the spreading light beam into a well-defined parallel beam of uniform intensity. The collimated light then passes through the first linear polarizer 212, which filters the light to create a specific polarization state. The first linear polarizer 212, mounted in a geared holder 228 and controlled by a stepper motor 230, can be precisely rotated to different angles to establish different initial polarization states. After polarization, the light beam enters the second collimator 214, which focuses the polarized light to a point optimized for coupling into the optical fiber. The focused, polarized light then enters the transmission fiber 222A of the optical fibre-based probe 206, which guides the light with minimal loss while maintaining the polarization state. Finally, the light exits the transmission fiber 222A and is directed onto the biological tissue 226 surfaces at a controlled angle and spot size, ensuring consistent tissue illumination for reliable measurements.
At step 304, the method 300 further includes collecting, by the optical fiber-based probe 206, light reflected from the biological tissue 226. The reception fiber 222B is placed at a carefully chosen angle relative to the surface of the biological tissue 226. The angle maximizes the amount of reflected light captured, balancing between signal strength and minimizing noise or stray light. Different tissue types scatter light differently. The optimal angle ensures that the fiber captures the most diagnostically relevant portion of the reflected light. For example, an angle of 45 degrees or 90 degrees may be used depending on the light-scattering properties of the biological tissue 226. When polarized light from the transmission fiber 222A interacts with the biological tissue 226, a portion of the light is reflected back. The reflected light contains information about the optical properties, such as anisotropy, depolarization, and polarizance. The reception fiber 222B collects this reflected light efficiently, ensuring minimal loss of the signal. The reception fiber 222B is positioned relative to the transmission fiber 222A to ensure accurate capture of light from the intended interaction zone. The reception fiber 222B and the transmission fiber 222A are separated by a precise distance and angle to prevent interference while ensuring an optimal overlap of the illumination and collection regions. The spatial relationship is important for maintaining the integrity of the light-tissue interaction data. Misalignment may lead to signal loss or contamination by stray light. The reflected light retains modified polarization states that are crucial for calculating optical parameters. The reception fiber 222B is designed to minimize depolarization during light transfer, preserving the polarization states altered by tissue interaction. The reception fiber 222B transmits the collected light to the reception module 204, where further processing occurs. The guided light maintains its intensity and polarization characteristics for accurate analysis.
At step 306, the method 300 further includes receiving and analysing, by a reception module, reflected light from the biological tissue 226. The reflected light is received from the reception fiber 222B, and then it is collimated by the reception collimator 216. The second linear polarizer 218 analyzes polarization states, and the photodetector 220 measures light intensity at each state and converts optical signals to electrical signals, thereby providing precise intensity measurements.
At step 308, the method 300 further includes adjusting, by at least one motor, polarization states of light to the plurality of predetermined angles. The first motor 230 and the second motor 236 consist of precision stepper motors coupled with bevel gears that provide accurate angular positioning of both polarizers (the first linear polarizer 212 in transmission module 202 and the second linear polarizer 218 in the reception module 204). The first motor 230 and the second motor 236 work synchronously to rotate both the linear polarizers. Each motor provides precise angular movement in 0.9 degrees steps. The bevel gear mechanism converts motor rotation to polarizer rotation. Real-time position feedback ensures accurate angle positioning.
At step 310, the method 300 further includes receiving, by a processor 106, a plurality of light intensity measurements from the reception module 204 corresponding to different combinations of the polarization states of the reflected light from the biological tissue 226. The reception module 204 collects light reflected from the biological tissue 226, which carries information about the tissue's optical properties. By systematically varying the polarization states of the incident light and detecting the corresponding reflected light intensities, the optical system 100 generates a dataset that reflects the interaction between the light and the biological tissue. Each combination of polarization states reveals unique aspects of the tissue's structural and optical characteristics, such as anisotropy, depolarization, and polarizance. The measurements are then sent to the processor for further analysis, where they are used to compute predefined optical parameters and characterize the biological tissue 226.
At step 312, the method 300 further includes calculating, by the processor, values for a plurality of predefined optical parameters based on the received light intensity measurements at the different polarization states of the reflected light. The calculation of predefined optical parameters begins with the processor 106 receiving light intensity measurements obtained at different polarization states from the reception module 204. The measurements are used to compute the elements of a Mueller matrix, which mathematically represents how the biological tissue 226 modifies the polarization state of the incident light. Once the matrix elements are calculated, the processor 106 uses them to derive optical parameters such as normalized anisotropy, anisotropy degrees, depolarization coefficient, linear polarizance, linear diattenuation, the orientation of maximum transmittance for linear polarizance, and orientation of maximum transmittance for linear diattenuation. The optical parameters are computed using established formulas. The calculated values of the optical parameters are then displayed in real-time through the GUI 120 enabling precise tissue characterization and differentiation between healthy and fibrotic tissues.
At step 314, the method 300 includes characterizing, by the processor 106, the biological tissue 226 based on the calculated values of the optical parameters. The processor 106 applies predefined algorithms to interpret the optical parameters, correlating them with the structural, biochemical, or functional characteristics of the biological tissue 226. For example, variations in birefringence may indicate changes in biological tissue alignment or composition, while scattering coefficients might reflect cellular density or morphology. The processor 106 then classifies the tissue into predefined categories, identifies abnormalities, or provides diagnostic insights. The characterization is essential for applications like detecting pathological conditions, assessing tissue health, or monitoring treatment responses, and the results are displayed on the GUI 120 for user interpretation.
At step 316, the method 300 includes generating, by the processor 106, an output indicating characterization of the biological tissue 226 based on the calculated values of the plurality of predefined optical parameters. The processor 106 first compiles all calculated optical parameters and presents them through the GUI 120 using intuitive visual representations. The output includes real-time dynamic gauges showing parameter values. The Mueller matrix elements are displayed in a 3x3 grid format, providing detailed information about tissue polarization properties. Additionally, the processor 106 generates a clear tissue classification result based on the machine learning model's analysis, displaying it prominently as either "Healthy Tissue" or "Fibrotic Tissue" along with a confidence percentage (e.g., 92% confidence in classification). For surgical guidance, the output includes visual indicators marking boundaries between healthy and fibrotic regions, enabling surgeons to precisely identify transition zones. The optical system 100 maintains a continuous update of these parameters and classifications, refreshing the display at regular intervals (after completing one measurement) to provide real-time feedback during surgical procedures. Historical data is also tracked and displayed as trend graphs, allowing medical professionals to monitor changes in tissue characteristics over time. Alert indicators are automatically triggered when parameters exceed predetermined thresholds, ensuring immediate attention to significant changes in tissue properties.
At step 318, the method 300 includes displaying, by the processor 106, the received light intensity measurements of the reflected light and the calculated values of the plurality of predefined optical parameters for the biological tissue on the GUI 120. The light intensity measurements, obtained from the reception module 204 at various polarization states, are first presented on the GUI 120, providing a visual representation of the raw data collected during the tissue analysis. The measurements serve as the foundational input for calculating predefined optical parameters such as normalized anisotropy, depolarization coefficient, linear polarizance, linear diattenuation, orientation of maximum transmittance for linear polarizance, and orientation of maximum transmittance for linear diattenuation. Once the processor 106 computes these parameters, the GUI 120 updates to display their values alongside the intensity data, offering a comprehensive view of the tissue's optical and structural characteristics. The GUI 120 may also include visual aids like graphs, numerical tables, or colour-coded indicators to highlight variations in the parameters and their correlation with the tissue condition (e.g., healthy or fibrotic). The real-time display enables medical professionals to monitor and interpret the data effectively, ensuring informed decision-making during surgical or diagnostic procedures.
Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe, and claim the present disclosure are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural. The word "exemplary" is used herein to mean "serving as an example, instance or illustration". Any embodiment described as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments and/or to exclude the incorporation of features from other embodiments. The word "optionally" is used herein to mean "is provided in some embodiments and not provided in other embodiments". It is appreciated that certain features of the present disclosure, 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 present disclosure, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable combination or as suitable in any other described embodiment of the disclosure. , Claims:CLAIMS
We claim:
1. A portable optical system (100) for characterization of a biological tissue (226), comprising:
a polarization-based optical device (102) comprising:
a transmission module (202) configured to automatically generate and direct a transmitted light at a plurality of predetermined angles onto a biological tissue;
a reception module (204) configured to automatically receive and analyze light reflected from the biological tissue (226);
an optical fiber-based probe (206) operatively connected to the transmission module (202) and the reception module (204), and configured to direct the transmitted light onto the biological tissue (226) and collect the reflected light from the biological tissue (226); and
at least one motor (230, 236) configured to automatically adjust polarization states to the plurality of predetermined angles; and
a processor operatively connected to the transmission module (202), the reception module (204), the optical fiber-based probe (206), and the at least one motor (230, 236) of the polarization-based optical device (102), the processor (106) configured to:
control the at least one motor (230, 236) to automatically adjust the polarization states to the plurality of predetermined angles;
receive, from the reception module (204), a plurality of light intensity measurements corresponding to different combinations of the polarization states;
calculate values for a plurality of predefined optical parameters based on the received light intensity measurements at the different polarization states and display the calculated values on a graphical user interface (GUI) (120);
characterize the biological tissue (226) based on the calculated values of the plurality of predefined optical parameters; and
generate an output indicating characterization of the biological tissue (226) on the GUI (120).
2. The portable optical system (100) as claimed in claim 1, wherein the predefined optical parameters comprise at least one of: normalized anisotropy, anisotropy degrees, depolarization coefficient, linear polarizance, linear diattenuation, orientation of maximum transmittance for linear polarizance, and orientation of maximum transmittance for linear diattenuation.
3. The portable optical system (100) as claimed in claim 1, wherein the transmission module comprises:
a light source (208) configured to emit light at a predetermined wavelength;
a first collimator (210) configured to collimate the emitted light;
a first linear polarizer (212) configured to receive the collimated light from the first collimator (210) and polarize the received collimated light at the plurality of predetermined angles; and
a second collimator (214) configured to focus the collimated polarized light as the transmitted light and direct the transmitted light to the optical fiber-based probe (206).
4. The portable optical system (100) as claimed in claim 1, wherein the reception module (204) comprises:
a reception collimator (216) configured to collimate the reflected light from the biological tissue (226);
a second linear polarizer (218) configured to receive the collimated light from the reception collimator (216) and polarize the reflected light at the plurality of predetermined angles; and
a photodetector (220) configured to measure intensity of the polarized reflected light.
5. The portable optical system (100) as claimed in claim 1, wherein the optical fiber-based probe (206) comprises:
a transmission fiber (222A) configured to direct the transmitted light received from the transmission module (202) onto the biological tissue (226); and
a reception fiber (222B) configured to collect the reflected light from the biological tissue (226) to further direct the reflected light to the reception module (204).
6. The portable optical system (100) as claimed in claim 1, wherein the processor (106) is further configured to:
perform real-time analysis of the biological tissue (226) characteristics;
identify boundaries between a healthy tissue region and a fibrotic biological tissue region; and
provide guidance for surgical interventions based on the characterization of the biological tissue (226).
7. The portable optical system (100) as claimed in claim 1, further comprises a trained machine learning model (110) communicatively connected to the processor (106), wherein the trained machine learning model (110) is configured to:
receive the calculated values for the plurality of predefined optical parameters as input;
compare the received calculated values with a training dataset (116); and
classify the biological tissue (226) as healthy or fibrotic based on the comparison of the received calculated values with the training dataset (116).
8. The portable optical system (100) as claimed in claim 7, wherein the training dataset (116) comprises:
ranges of values of the plurality of predefined optical parameters for healthy tissue samples; and
ranges of values of the plurality of predefined optical parameters for fibrotic tissue samples.
9. The portable optical system (100) as claimed in claim 1, wherein the processor is further configured to:
generate the graphical user interface (GUI) (120);
display the calculated values for the plurality of predefined optical parameters on the GUI (120); and
provide real-time tissue characterization feedback on the GUI (120).
10. A method (300) for characterizing biological tissue using a portable optical system (100), the method (300) comprising:
generating and directing, by a transmission module (202) and an optical fiber-based probe (206), polarized light at a plurality of predetermined angles onto a biological tissue (226);
collecting, by the optical fiber-based probe (206), light reflected from the biological tissue (226);
receiving and analyzing, by a reception module (204), the reflected light from the biological tissue (226);
adjusting, by at least one motor, polarization states of the reflected light to the plurality of predetermined angles;
receiving, by a processor (106), a plurality of light intensity measurements from the reception module (204) corresponding to different combinations of the polarization states of the reflected light from the biological tissue (226);
calculating, by the processor (106), values for a plurality of predefined optical parameters based on the received light intensity measurements at the different polarization states of the reflected light;
characterizing, by the processor (106), the biological tissue based on the calculated values of the plurality of predefined optical parameters;
generating, by the processor (106), an output indicating characterization of the biological tissue (226) based on the calculated values of the plurality of predefined optical parameters; and
displaying, by the processor (106), the received light intensity measurements of the reflected light and the calculated values of the plurality of predefined optical parameters for the biological tissue (226) on a graphical user interface (GUI) (120).