Breast dynamic optical tomography system based on fluorescence image guidance

Abstract

The disclosure provides a breast dynamic optical tomography system based on fluorescence image guidance, comprising: a first lifting platform for adjusting the height of a light source module and a detection module; a second lifting platform for controlling the movement of a pressing plate; one side of the pressing plate is fixed on the second lifting platform, and the other side is used for pressing the tissue to be detected; the light source module generates detection light; the detection module samples the surface emission light of the detection light after passing through the tissue to be detected to obtain each wavelength emission light image; a host module processes the surface fluorescence image by using a fluorescence diffuse optical tomography method to obtain a segmentation image; the time sequence of the surface diffuse light image is demodulated to obtain the time sequence of the surface diffuse light image corresponding to each wavelength; and a diffuse optical tomography method is used to process the segmentation image and the time sequence of the surface diffuse light image corresponding to each wavelength to obtain the time sequence of the three-dimensional image of the absorption coefficient change corresponding to each wavelength.

Description

Technical Field

[0001] This disclosure relates to the fields of computer technology and tissue optical imaging technology, and more specifically, to a dynamic optical tomography system for breast based on fluorescence image guidance. Background Technology

[0002] With increasing life pressures, breast cancer has become the leading cause of cancer death worldwide, making early detection and control crucial. Although imaging methods are widely used for early screening and dynamic assessment of breast cancer, these methods have many limitations and are not suitable for routine screening and dynamic assessment: for example, mammography involves ionizing radiation; ultrasound imaging has sensitivity issues; and magnetic resonance imaging is too expensive for routine screening.

[0003] In recent years, diffuse optical tomography (DOT) has utilized the high penetration depth of diffused light within tissues to reconstruct the spatial distribution of optical parameters within the breast, detect important biochemical parameters, and characterize hemodynamic responses. As an emerging optical imaging method, DOT offers advantages such as no ionizing radiation, non-invasiveness, provision of physiological information, and continuous dynamic measurement. However, the pathological inverse problem of DOT can severely degrade the reconstructed spatial resolution. In particular, for early screening of breast lesions, the phantom calibration strategy used in static DOT imaging often suffers from accuracy and adaptability issues, frequently causing significant artifacts from anatomical structures, thus severely interfering with the sensitivity and specificity of diagnosis.

[0004] Fluorescence diffusion optical tomography (FDOT) is an extension of diffusion optical tomography. During imaging, a near-infrared fluorescent probe or fluorescent reagent is added, and the image is illuminated with a light source of approximately the excitation wavelength of the fluorescent marker. The three-dimensional distribution image of the fluorescent marker is obtained by measuring the fluorescence information from the surface of the tissue under test. Because the aggregation effect of the fluorescent contrast agent can produce high fluorescence contrast, it can provide prior information about the spatial distribution of the lesion area. However, the non-targeted fluorescent agent indocyanine green used clinically has low quantum efficiency, and the sensitivity and specificity of the imaging results further decrease during metabolism, making long-term dynamic monitoring difficult.

[0005] Therefore, there is an urgent need to find a system that can perform high-quality dynamic imaging and reconstruction of breast tissue. Summary of the Invention

[0006] In view of this, the present disclosure provides a dynamic optical tomography system for breast based on fluorescence image guidance.

[0007] This disclosure provides a dynamic optical tomography system for breast based on fluorescence image guidance, comprising: a first lifting platform for adjusting the height of a light source module and a detection module, wherein the light source module and the detection module are located on both sides of the tissue to be detected, and the tissue to be detected includes the breast.

[0008] The second lifting platform is used to control the movement of the pressure plate.

[0009] The aforementioned pressure plate is fixed on one side to the aforementioned second lifting platform, and on the other side is used to compress the aforementioned tissue to be tested;

[0010] The aforementioned light source module is used to generate probe light of different wavelengths and positions under different frequency modulations;

[0011] The aforementioned detection module is used to sample the surface emitted light after the aforementioned detection light passes through the aforementioned tissue to be detected, and obtain emitted light images of each wavelength corresponding to the emitted light intensity signal. The emitted light images include a time series of surface fluorescence images corresponding to the excited fluorescence of the aforementioned tissue to be detected and surface diffuse light images corresponding to the aforementioned tissue to be detected under the pressure of the aforementioned pressure plate.

[0012] The host module is used to process the surface fluorescence image using fluorescence diffusion optical tomography to obtain a three-dimensional image of the fluorescence yield distribution inside the tissue and to segment it to obtain a segmented image. It also demodulates the time series of the surface diffusion light image to obtain a time series of surface diffusion light images corresponding to each wavelength. Finally, it uses diffusion optical tomography to process the segmented image and the time series of the surface diffusion light images corresponding to each wavelength to obtain a time series of three-dimensional images showing the change of absorption coefficients corresponding to each wavelength relative to the initial pressurization time.

[0013] According to embodiments of this disclosure, the host module performs the following operations to process the time series of the segmented image and the surface diffuse light image corresponding to each wavelength using diffusion optical tomography, thereby obtaining a time series of three-dimensional images showing the change of absorption coefficients corresponding to each wavelength relative to the initial pressurization time:

[0014] Based on the target matrix and the time series of surface diffuse light images corresponding to each wavelength, a time series of three-dimensional images of the absorption coefficient changes corresponding to each wavelength relative to the initial pressurization time is obtained.

[0015] According to an embodiment of this disclosure, the first preset value is 0.

[0016] According to embodiments of this disclosure, the host module performs the following operations to process the surface fluorescence image using the fluorescence diffusion optical tomography method, obtain a three-dimensional image of the fluorescence yield distribution inside the tissue, and segment it to obtain a segmented image:

[0017] The surface fluorescence images were processed using fluorescence diffusion optical tomography to obtain a three-dimensional image of the fluorescence yield distribution inside the tissue.

[0018] Using the Otsu's method, based on the three-dimensional image of fluorescence yield distribution within the tissue, the preset threshold between-class variance and within-class variance are calculated to obtain the target threshold.

[0019] Based on the target threshold, the region of interest is extracted from the three-dimensional image of the fluorescence yield distribution within the tissue to obtain the segmented image.

[0020] According to embodiments of this disclosure, the light source module includes:

[0021] The lower-level control unit is used to receive control commands issued by the host module and communicate with the LED driver unit through a preset communication mechanism to send the control commands to the LED driver unit.

[0022] The aforementioned LED driving unit is used to generate driving signals according to the aforementioned control instructions;

[0023] The light-emitting diode lamp board unit is used to generate probe light modulated at different frequencies according to the above-mentioned driving signal.

[0024] According to an embodiment of this disclosure, the above-mentioned light-emitting diode lamp board unit includes: a lamp board, a positioning lamp, and a detection lamp;

[0025] The positioning lights are arranged on circles of different radii with the bottom center of the light panel as the center, and the detection lights are arranged between the positioning lights and the bottom of the light panel. The detection lights are arranged in a triangular pattern on the light panel.

[0026] The aforementioned detection light includes a first detection light emitted when both the aforementioned positioning light and the aforementioned detection light are driven to emit light, and the aforementioned emitted image also includes a positioning image;

[0027] The aforementioned detection module performs the following operations to sample the emitted light after the detection light passes through the tissue to be detected, thereby obtaining an emitted light image of the specified wavelength corresponding to the emitted light intensity signal:

[0028] The emitted light after the first detection light passes through the tissue to be detected is sampled to obtain the positioning image.

[0029] The host module is also used to determine the size of the area of ​​the tissue to be detected based on the aforementioned positioning image.

[0030] According to embodiments of this disclosure, the system further includes:

[0031] The pressure measurement module is used to monitor the pressure when the pressure plate presses the tissue to be tested, and upload the signal corresponding to the pressure to the host module.

[0032] The aforementioned host module is also used to display the signal corresponding to the aforementioned pressure in real time.

[0033] According to embodiments of this disclosure, the pressure measurement module includes:

[0034] A pressure sensor is placed between the tissue to be detected and the lamp panel to collect pressure signals;

[0035] The transmitter is used to convert the pressure signal into a weight signal and upload the weight signal to the host unit.

[0036] According to embodiments of this disclosure, the detection light includes a second detection light;

[0037] The aforementioned detection module performs the following operations to sample the emitted light after the detection light passes through the tissue to be detected, thereby obtaining emitted light images of each wavelength corresponding to the emitted light intensity signal:

[0038] The emitted light of the second probe light after passing through the tissue to be detected is sampled to obtain a fluorescence reference image;

[0039] By combining the tissue to be tested with a fluorescent agent, and after the second probe light passes through the tissue to be tested, the fluorescence emitted from the tissue to be tested is sampled to obtain the surface fluorescence image.

[0040] According to embodiments of this disclosure, the detection light includes a third detection light;

[0041] The aforementioned detection module performs the following operations to sample the emitted light after the detection light passes through the tissue to be detected, thereby obtaining emitted light images of each wavelength corresponding to the emitted light intensity signal:

[0042] When the pressure of the pressure plate pressing the tissue to be tested reaches the preset pressure, the emitted light of the third probe light after passing through the tissue to be tested is sampled to obtain the surface diffuse light image time series.

[0043] According to the fluorescence image-guided dynamic optical tomography system for breast tissue provided in this disclosure, after obtaining the emitted light images at each wavelength corresponding to the emitted light intensity signal, the high fluorescence contrast is generated by the aggregation effect of the fluorescent contrast agent during reconstruction using fluorescence diffusion optical tomography, allowing for accurate identification of cancerous areas. Therefore, the host module uses fluorescence diffusion optical tomography to obtain a three-dimensional image of the fluorescence yield distribution within the tissue and performs segmentation processing to obtain a segmented image. This provides prior location information for diffusion optical tomography reconstruction, enabling the diffusion optical tomography method to reconstruct only the region of interest with prior information, reducing the number of unknown parameters and lowering the underdeterminacy and pathological nature of the problem. Finally, the time series of the segmented image and the surface diffusion light images at each wavelength are processed using diffusion optical tomography to obtain a time series of three-dimensional images showing the change in absorption coefficients corresponding to each wavelength relative to the initial pressurization time, thus realizing dynamic high-quality imaging of breast tissue using diffusion optical tomography. This system and method can improve dynamic imaging quality and reconstruction accuracy, thereby effectively enhancing the reliability of diffusion optical tomography in assisting early tumor diagnosis. Attached Figure Description

[0044] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0045] Figure 1 A schematic diagram of a fluorescence image-guided dynamic optical tomography system for the breast according to an embodiment of the present disclosure is shown.

[0046] Figure 2 A schematic diagram of a detection module according to an embodiment of the present disclosure is shown; and

[0047] Figure 3 The diagram illustrates a host module demodulating an emitted light intensity signal according to an embodiment of the present disclosure. Detailed Implementation

[0048] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0049] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0050] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0051] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0052] In the embodiments disclosed herein, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security and network security.

[0053] In the embodiments disclosed herein, user authorization or consent is obtained before acquiring or collecting user personal information.

[0054] The breast dynamic optical tomography system based on fluorescence image guidance provided in this disclosure can utilize the specificity of fluorescent dyes and the specific signal amplification in FDOT imaging to achieve preliminary segmentation of the tumor target region, eliminate non-target interference, and enhance the quantitative reconstruction of the DOT absorption coefficient. Furthermore, it can be combined with a dynamic DOT imaging strategy with self-reference characteristics to achieve continuous dynamic monitoring of absorption changes in the imaging region.

[0055] Figure 1 A schematic diagram of a fluorescence image-guided dynamic optical tomography system for the breast is shown according to an embodiment of the present disclosure.

[0056] like Figure 1 As shown, the breast dynamic optical tomography system 100 based on fluorescence image guidance may include: a first lifting platform 110, a second lifting platform 120, a detection module 130, a light source module 140, a pressure plate 150, and a host module 160.

[0057] The first lifting platform 110 can be used to adjust the height of the light source module 140 and the detection module 130, wherein the light source module 140 and the detection module 130 are located on both sides of the tissue to be detected.

[0058] According to embodiments of this disclosure, the object can be a human or an animal. The tissue to be detected can be breast tissue from an animal or a human. The first lifting platform 110 can adjust the height of the light source module 140 and the detection module 130 according to the height of the object, and can also adjust the distance between the two modules.

[0059] The second lifting platform 120 can be used to control the movement of the pressure plate 150. Specifically, the second lifting platform 120 can control the movement direction, speed, acceleration, and deceleration of the pressure plate 150 according to the instructions sent by the main module 160.

[0060] One side of the pressure plate 150 can be fixed to the second lifting platform 120, and the other side is used to compress the tissue to be tested. The pressure plate 150 can be made of transparent acrylic material.

[0061] The light source module 140 can be used to generate probe light of different wavelengths and positions under different frequency modulations. The light source module 140 can also use the probe light to irradiate the tissue to be tested.

[0062] For example, the light source module 140 can generate probe light with different frequency modulations according to the frequency encoding rules and drive current magnitude set by the client through the host module 160.

[0063] The detection module 130 can be used to sample the surface emitted light after the probe light passes through the tissue to be detected, and obtain an emitted light image corresponding to the emitted light intensity signal. The emitted light image includes a time series of a surface fluorescence image corresponding to the excited fluorescence of the tissue to be detected and a surface diffuse light image corresponding to the tissue to be detected under pressure. The emitted light intensity signal includes transmission information containing the parameter variation characteristics of the tissue to be detected.

[0064] For example, the detection module 130 can perform high frame rate sampling on the transmission information that carries the parameter variation characteristics of the breast tissue after passing through the breast tissue.

[0065] The host module 160 can be used to process surface fluorescence images using fluorescence diffusion optical tomography to obtain a three-dimensional image of the fluorescence yield distribution inside the tissue and perform segmentation processing to obtain a segmented image; demodulate the time series of the surface diffusion light image to obtain a time series of the surface diffusion light image corresponding to each wavelength; and use diffusion optical tomography to process the segmented image and the time series of the surface diffusion light image corresponding to each wavelength to obtain a time series of a three-dimensional image of the change of the absorption coefficient corresponding to each wavelength relative to the initial pressurization time.

[0066] The three-dimensional image representing the change in absorption coefficient is a representation of the three-dimensional image corresponding to the amount of change in absorption coefficient. For example, the time series of the three-dimensional images of the absorption coefficient change corresponding to each wavelength can be: a time series of the three-dimensional images of the absorption coefficient change corresponding to the first wavelength, a time series of the three-dimensional images of the absorption coefficient change corresponding to the second wavelength, and a time series of the three-dimensional images of the absorption coefficient change corresponding to the third wavelength. The first wavelength, the second wavelength, and the third wavelength can be selected according to the actual situation and are not limited here.

[0067] According to embodiments of this disclosure, since the DOT and FDOT methods are similar in imaging principle and data acquisition method, the detection module 130 and the light source module 140 can be used together.

[0068] For example, the host module 160 can use FDOT to process the surface fluorescence image to obtain a three-dimensional image of the fluorescence yield distribution within the tissue. Then, the region of interest can be extracted from this three-dimensional image to obtain a segmented image. Because FDOT has high sensitivity, the aggregation effect of the fluorescent contrast agent during FDOT reconstruction produces high fluorescence contrast, enabling accurate localization of cancerous areas. This provides reliable prior location information, and therefore, the resulting segmented image accurately reflects the background and cancerous areas corresponding to the tissue being detected.

[0069] According to embodiments of this disclosure, the three-dimensional image of the absorption coefficient variation includes information reflecting the characteristics of tumor lesions. Therefore, DOT can obtain information on the characteristics of tumor lesions, especially information on the characteristics of tumor lesions that change over time, based on the time series of the three-dimensional image of the absorption coefficient variation corresponding to each wavelength.

[0070] According to embodiments of this disclosure, the host module 160 processes the fluorescence image using fluorescence diffusion optical tomography (FDOT) to obtain a segmented image. Then, using FDOT tomography, it processes the time series of the segmented image and the surface diffuse light image corresponding to each wavelength to obtain a time series of three-dimensional images showing the change in absorption coefficients corresponding to each wavelength relative to the initial pressure application time. This allows for demodulation of the emitted light intensity signal corresponding to the fluorescence image. Furthermore, the prior information for DOT reconstruction included in the FDOT imaging results guides DOT reconstruction, achieving joint DOT and FDOT imaging. This effectively compensates for the deficiencies in both DOT and FDOT reconstruction. Further, acquiring physiological state information of breast tissue based on images of dynamic changes in absorption coefficients under pressure changes can meet the spatiotemporal resolution and quantitative reconstruction requirements for early breast lesion screening, significantly improving the accuracy, reliability, and practicality of assisted early breast lesion screening and promoting its application in the clinical field of breast lesion screening.

[0071] According to the fluorescence image-guided dynamic optical tomography system for breast tissue provided in this disclosure, after obtaining the emitted light images at each wavelength corresponding to the emitted light intensity signal, the high fluorescence contrast is generated by the aggregation effect of the fluorescent contrast agent during reconstruction using fluorescence diffusion optical tomography, enabling accurate identification of the cancerous area. Therefore, the in-situ host module processes the surface fluorescence image using fluorescence diffusion optical tomography to obtain a segmented image that accurately reflects the background area and cancerous area corresponding to the breast tissue to be detected. Then, the time series of the segmented image and the surface diffuse light image corresponding to each wavelength are processed using diffusion optical tomography to obtain a time series of three-dimensional images showing the change of absorption coefficients corresponding to each wavelength relative to the initial pressure time. This realizes the segmented image obtained based on fluorescence diffusion optical tomography, providing prior location information for diffusion optical tomography reconstruction. This allows diffusion optical tomography to reconstruct only the region of interest with prior information, reducing the number of unknown parameters, lowering the underdeterminacy and pathological nature of the problem, and simultaneously achieving dynamic high-quality imaging of breast tissue using diffusion optical tomography. This system can improve dynamic imaging quality and reconstruction accuracy, thereby effectively enhancing the reliability of diffusion optical tomography in assisting early tumor diagnosis.

[0072] like Figure 1 As shown, the light source module 140 may include a lower-level control unit 141, a light-emitting diode driving unit, and a light-emitting diode lamp board unit 142.

[0073] like Figure 1 As shown, the LED lamp board unit 142 may include: lamp board 1421, positioning lamp 1422 and detection lamp 1423.

[0074] exist Figure 1 In the lamp panel 1421, the positioning lights 1422 are arranged on circles of different radii with the bottom center of the lamp panel 1421 as the center. The detection lights 1423 are arranged between the positioning lights 1422 and the bottom of the lamp panel 1421. The detection lights 1423 are arranged in a triangular pattern on the lamp panel 1421.

[0075] According to embodiments of this disclosure, the positioning lamp 1422 can be flexibly arranged on circles of different radii centered at the bottom center of the lamp plate 1421 to adapt to different detection needs. Before performing formal detection using the breast dynamic optical tomography system 100 based on fluorescence image guidance provided in embodiments of this disclosure, a pre-detection is first required to determine the size of the tissue to be tested.

[0076] During the pre-detection process, all light sources are illuminated. The detection light may include the first detection light emitted when both the positioning light 1422 and the detection light 1423 are driven to emit light. The emitted light intensity signal may include the first emitted light intensity signal, and the emitted image may also include a positioning image, which corresponds to the first emitted light intensity signal. The first detection light includes the light emitted by the positioning light 1422 and the light emitted by the detection light 1423.

[0077] exist Figure 1 In this process, the detection module 130 can sample the emitted light after the detection light passes through the tissue to be detected by performing the following operations to obtain emitted light images of each wavelength corresponding to the emitted light intensity signal: sampling the emitted light after the first detection light passes through the tissue to be detected to obtain a positioning image corresponding to the first emitted light intensity signal, thus obtaining a positioning image. The host module 160 can also be used to determine the size of the area of ​​the tissue to be detected based on the positioning image.

[0078] When the host module 160 determines the size of the tissue to be detected based on the positioning image, the uncovered positioning lights 1422 will appear as light saturation in the high-speed camera image of the detection module 130. This phenomenon allows for precise determination of the boundary range of the tissue to be detected. The radius of the positioning lights 1422 can be adjusted according to the different dimensions of the object (e.g., the human body) to meet the detection requirements of different objects (e.g., the human body). The positioning lights 1422 are distributed on circles of different radii centered at the bottom center of the light panel 1421, enabling precise detection of different areas. This configuration effectively improves the accuracy and flexibility of the detection, ensuring the reliability and precision of the detection results.

[0079] The detector lamp 1423 can generate near-infrared light of a specific wavelength as the incident light source (i.e., detector light) of the system.

[0080] For example, after pre-detection to determine the size of the tissue to be detected, the fluorescent agent ICG can be used when imaging the tissue using the FDOT reconstruction method. Taking advantage of the characteristics of ICG—excitation wavelength of 780nm and fluorescence emission wavelength of 830nm—the fluorescence image-guided dynamic optical tomography system 100 for breast tissue can use a tri-color LED (Light Emitting Diode) as the light source (i.e., as the probe lamp 1423). This light source can output near-infrared light at 730nm, 775nm, and 855nm. The fluorescence image-guided dynamic optical tomography system 100 for breast tissue uses a steady-state light source, meaning the light intensity remains stable and can be fully or partially illuminated. When the tissue to be detected is breast tissue, the probe lamps 1423 can be arranged in a triangular pattern according to the physiological structure and shape of the breast, specifically ten lamps with a spacing of 12mm. The incident light source can be modulated with square wave signals of different frequencies and driven by different magnitudes of current to control the light intensity.

[0081] After pre-detection to determine the size of the tissue to be detected, when imaging the tissue using the FDOT reconstruction method, the emitted light intensity signal may include a second and a third emitted light intensity signal, and the probe light may include a second probe light. The second probe light can be, for example, near-infrared light of a specific wavelength (775nm) generated when the probe lamp 1423 is a tri-color LED. The detection module 130 can sample the emitted light after the probe light passes through the tissue to obtain emitted light images of each wavelength corresponding to the emitted light intensity signal by performing the following operations: sampling the emitted light after the second probe light passes through the tissue to obtain a fluorescence reference image corresponding to the second emitted light intensity signal; and sampling the fluorescence emitted from the tissue after the second probe light passes through it, combining the tissue to be detected with a fluorescent agent, to obtain a surface fluorescence image corresponding to the third emitted light intensity signal.

[0082] For example, after the second probe light passes through the tissue to be detected, the background light emitted from the tissue to be detected can be sampled to obtain a second emitted light intensity signal, and then a fluorescence reference image can be obtained; after the tissue to be detected is combined with a fluorescent agent, after the second probe light passes through the tissue to be detected, the fluorescence emitted from the tissue to be detected can be sampled to obtain a third emitted light intensity signal, and then a surface fluorescence image can be obtained.

[0083] At this time, the host module 160 can perform the following operation to process the surface fluorescence image using the fluorescence diffusion optical tomography method to obtain a segmented image: process the fluorescence reference image and the surface fluorescence image using the fluorescence diffusion optical tomography method to obtain a segmented image.

[0084] The lower-level control unit 141 can receive control commands from the host module 160 and communicate with the LED driver unit through a preset communication mechanism to send the control commands to the LED driver unit. The LED driver unit can generate drive signals according to the control commands. The LED lamp board unit 142 can generate detection light modulated at different frequencies according to the drive signals.

[0085] For example, the lower-level control unit 141 can receive instructions from the host module 160 and communicate with the LED driver unit via I2C communication to control each LED (i.e., the detector lamp 1423) to be modulated with square wave information of different frequencies. Different levels can be adjusted via digital potentiometers to change the driving current and control the light intensity. Specifically, the breast dynamic optical tomography system 100 based on fluorescence image guidance described above has ten detector lamps 1423, each with three wavelengths; therefore, 30 modulation frequencies are required. Based on the sampling theorem, the frame rate characteristics of the high-speed camera (~500fps), and the need to avoid the influence of higher harmonics between square waves, 30 frequencies are selected, alternating between 5-32Hz and frequency sequences increasing in 3Hz intervals.

[0086] For example, the lower-level control unit 141 can use a DE10-Nano board, which is mainly used to generate the modulation signal of the LED driver unit, the reference signal of the demodulator, and the resistance information of the digital potentiometer, i.e., the magnitude of the drive current. The LED driver unit can use a WD3100 driver chip to achieve constant current drive, and combine it with an AD5259 digital potentiometer to achieve a large dynamic range adjustment of the drive current.

[0087] like Figure 1 As shown, the breast dynamic optical tomography system 100 based on fluorescence image guidance may further include: a pressure measurement module 170.

[0088] The pressure measurement module 170 can be used to monitor the pressure when the pressure plate 150 compresses the tissue to be tested, and upload the pressure-corresponding signal to the host module 160. The host module 160 can also be used to display the pressure-corresponding signal in real time.

[0089] The pressure measurement module 171 may include a pressure sensor 171 and a transmitter.

[0090] A pressure sensor 171, positioned between the tissue to be detected and the lamp panel 1421, can be used to acquire pressure signals. A transmitter can be used to convert the pressure signal into a weight signal and upload the weight signal to the host unit.

[0091] For example, when the tissue to be tested is breast tissue, the pressure measurement module 171 can monitor the pressure when the breast is compressed and upload it to the host module 160 for real-time display.

[0092] For example, when the tissue to be detected is breast tissue, after pre-detection to determine the size of the tissue to be detected, before imaging the tissue using the DOT reconstruction method, pressure sensor 171 can be placed between the breast tissue and lamp plate 1421 to collect pressure. The transmitter converts the collected pressure signal into a readable weight signal and uploads it to the host module 160 via RS485 communication. When the collected pressure reaches the pressure threshold (i.e., the preset pressure) set by the host module 160, the trigger program causes the second lifting platform 120 to control the pressure plate 150 to stop pressing down and maintain the current state.

[0093] In the DOT reconstruction method, when imaging the tissue to be tested, the emitted light intensity signal may include a fourth emitted light intensity signal, and the probe light may include a third probe light.

[0094] The detection module 130 samples the emitted light after the probe light passes through the tissue to be detected by performing the following operations to obtain emitted light images of each wavelength corresponding to the emitted light intensity signal: When the pressure of the pressure plate 150 pressing the tissue to be detected reaches a preset pressure, the emitted light after the third probe light passes through the tissue to be detected is sampled to obtain a time series of surface diffuse light images corresponding to the fourth emitted light intensity signal. The initial pressure application time is the initial moment when the pressure of the pressure plate pressing the tissue to be detected reaches the preset pressure, at which point the detection module begins to acquire the time series of surface diffuse light images.

[0095] When selecting a pressure threshold (i.e., preset pressure), the effect of the degree of compression on blood distribution within vascular compartments must be considered. High-intensity compression can cause almost all blood in vascular compartments (including arteries) to be expelled, while low-intensity compression may only expel blood from veins and capillaries. Therefore, when local pressure is increased in a region, HbT (total hemoglobin) in that region decreases. Furthermore, the spatial pattern of blood redistribution is affected by the presence of inclusions of varying stiffness (such as tumors). For example, interstitial pressure in breast cancer is known to be increased compared to healthy breast tissue (interstitial hypertension). This increase results in a maximum reduction in HbT at the tumor site. Notably, the mechanical and hemodynamic responses of the breast to initial and subsequent compressions differ, even when the amplitude and duration of compression are the same. This difference is attributed to the hysteretic and viscoelastic properties of breast tissue. Specifically, the pressure sensor 171 can be an Allison AR-N101 plate pressure sensor, and the transmitter can be a TW20A high-precision transmitter with a pressure range of 200N and an accuracy of up to 0.5%. When the pressure plate 150 is pressed down, the measured pressure value can be displayed on the transmitter screen and simultaneously transmitted to the host module 160 via RS485 for display on the host computer.

[0096] Figure 2 A schematic diagram of a detection module according to an embodiment of the present disclosure is shown.

[0097] like Figure 2 As shown, Figure 1 The detection module 130 may include a high-speed camera 131, a lens 132, and a filter unit. When the tissue to be detected is breast tissue, the detection module 130 can acquire the emitted light intensity signal carrying the optical parameter change information of the breast tissue at millisecond-level exposure times, and the acquired image is uploaded to the host module 160 for storage. As the receiving end of the system, the high frame rate and high dynamic range of the high-speed camera 131 are used to achieve high-speed acquisition of high frame rate image signals, which greatly improves the temporal resolution of signal acquisition, while effectively suppressing the influence of ambient light on the measurement results and improving the measurement signal-to-noise ratio. Acquiring a single image signal at millisecond-level exposure times can effectively avoid camera saturation problems caused by light leakage from small breasts or reflected light from the lamp board. The high-speed camera 1331 is equipped with a standard C-mount camera lens 132, and the filter unit includes a filter wheel and a filter 1331, which is used to switch the filter 1331.

[0098] When the probe light 1423 is an LED light, the probe light generated by the probe light 1423, after passing through the tissue to be detected, can be captured by the high-speed camera 131 after passing through the filter unit and the optical lens 132. By controlling the rotation of the filter wheel, different filters 1331 can be selected to switch between different measurements. Specifically, when performing DOT imaging, a lens 132 without a filter 1331 is used; when performing FDOT imaging and measuring weak fluorescence signals (e.g., the third emitted light intensity signal), a lens 132 equipped with a filter 1331 is used. When using ICG in conjunction with the tissue to be detected, the quantum efficiency of ICG is 0.016, requiring the transmittance of the filter 1331 to be less than 10 for 780±10 nm. -4 For 830±10nm, which is greater than 0.9, a lens 132 equipped with an interference bandpass filter 1331 of FF01-832 / 37-14 (Semrock) can be used to filter out the excitation light signal. The transmittance of the filter 1331 between 813.5-850.5nm is greater than 93%.

[0099] exist Figure 1 In this system, the host module 160 can also be used to set system parameters through a human-machine interface and to perform three-dimensional reconstruction of breast tissue based on the corresponding light intensity change information obtained by fully parallel demodulating the emitted light intensity signal (i.e., emitted image). The host module 160 can use relevant software (e.g., LabVIEW software) to set the human-machine interface. To improve its practicality, the interface can be designed in sections according to different functions. The human-machine interface mainly includes three parts: the light source section, the detection section, and the pressure feedback and pressure plate control section. The light source section is used to send configuration information such as the illumination mode, modulation frequency, and light intensity adjustment of the light source array to the lower-level control unit 141 to control the modulation frequency and driving current of the light-emitting diode driving unit. The detection section is used to control the exposure time, integration time, and storage location of the high-speed camera 131. The pressure feedback and pressure plate control section can display the collected pressure in real time, and control the movement of the second lifting platform 120 and the pressure plate 150 after the preset pressure. It can control the direction, speed and acceleration / deceleration of the pressure plate 150. When the pressure value reaches the preset pressure, it automatically controls the pressure plate 150 to stop moving.

[0100] Figure 3 The diagram illustrates a host module demodulating an emitted light intensity signal according to an embodiment of the present disclosure.

[0101] like Figure 3As shown, in terms of imaging methods, the host module 160 can demodulate the light intensity information 302 of the surface diffuse light image 301 (i.e., the emitted light intensity signal) acquired by the high-speed camera 131 according to the principle of spectrum shifting, and then perform three-dimensional reconstruction of the demodulated information. Although the intensity of the diffuse reflected light signal emitted from the tissue is weak, its frequency is consistent with the modulation frequency of the probe light. Therefore, this characteristic can be used to modulate the light source at the irradiation end, and then demodulate it at the detection end, thereby achieving the separation of optical flux information under different wavelength light source excitation. The measured optical flux data is used to reconstruct the optical parameters inside the tissue.

[0102] The demodulation process is as follows Figure 3 As shown, firstly, a temporal Fourier transform is performed on each pixel in the surface diffuse light image to separate the spectral components at different modulation frequencies. The amplitudes of these spectral components correspond to the intensities of the light source at different modulation frequencies. Next, these spectral components obtained from the Fourier transform are filtered to retain the fundamental frequency and third harmonic components of each modulation frequency. The bandwidth can be selected as 1 Hz. Finally, an inverse Fourier transform is performed on the filtered components to reconstruct the light intensity information.

[0103] like Figure 3 As shown, by using a high-speed camera to demodulate the image frames of frequency division multiplexing output information, the organic integration of diffusion optical tomography (DOT) and fluorescence diffusion tomography (FDOT) technologies is achieved, which not only improves the efficiency and signal-to-noise ratio of data acquisition, but also improves the spatial resolution and quantification of imaging results.

[0104] According to embodiments of this disclosure, during camera imaging, each pixel can be considered a detector location, whose main task is to capture and record the emitted light signal. Before image reconstruction, detector selection must be performed, which involves merging N×N pixels into a superpixel as the new detector location. This merging helps reduce the complexity of data processing and improves the efficiency of image reconstruction. The number of detectors should be selected according to the actual situation to balance image quality and computational cost. The FDOT reconstruction process and DOT reconstruction process are described in detail below using S source locations (i.e., detector lamp locations) and D detector locations as examples. Here, S can be, for example, 6, and D can be 12.

[0105] During FDOT reconstruction, the host module 160 can perform the following operations to process the surface fluorescence image using fluorescence diffusion optical tomography (FDOT) to obtain a three-dimensional image of the fluorescence yield distribution within the tissue, and then segment it to obtain a segmented image: Processing the surface fluorescence image using FDOT to obtain a three-dimensional image of the fluorescence yield distribution within the tissue; calculating preset threshold inter-class variance and intra-class variance based on the three-dimensional image of the fluorescence yield distribution within the tissue using the maximum inter-class variance method to obtain a target threshold; and extracting the region of interest from the three-dimensional image of the fluorescence yield distribution within the tissue based on the target threshold to obtain a segmented image. Specifically, processing the surface fluorescence image using FDOT to obtain a three-dimensional image of the fluorescence yield distribution within the tissue includes: processing the fluorescence reference image and the surface fluorescence image using FDOT to obtain a three-dimensional image of the fluorescence yield distribution within the tissue.

[0106] For example, a threshold can be initialized based on a three-dimensional image of fluorescence yield distribution within the tissue. Pixels can be divided into background and target classes based on the threshold, and the intra-class variance and inter-class variance can be calculated. By iterating through each threshold (0 to 255), the optimal threshold that maximizes the inter-class variance is found, which is the target threshold.

[0107] According to embodiments of this disclosure, the preset threshold can be selected based on actual circumstances, and is not limited thereto.

[0108] According to embodiments of this disclosure, after processing the surface fluorescence image using fluorescence diffusion optical tomography to obtain a three-dimensional image of the fluorescence yield distribution within the tissue, a threshold is initialized based on the three-dimensional image of the fluorescence yield distribution within the tissue using the maximum inter-class variance method. Pixels are then divided into background and target classes based on the threshold, and the intra-class variance and inter-class variance are calculated. Each threshold (0-255) is iterated to find the optimal threshold that maximizes the inter-class variance, which is the target threshold. Based on the target threshold, the region of interest is extracted from the three-dimensional image of the fluorescence yield distribution within the tissue to obtain a segmented image. This enables the spatial location of the tumor tissue lesion from the fluorescence yield reconstruction image of FDOT to obtain a segmented image. This segmented image can then provide prior location information for DOT reconstruction, effectively improving the reliability of DOT in assisting the early diagnosis of breast tumors.

[0109] For example, when performing FDOT reconstruction, the source is located at r s Detection at r d fluorescence density Φ at the location m (r d r s The dV of all phosphor elements can be considered as the integral of the total volume, and thus can be expressed as formula (1):

[0110] Φm (r d r s )=∫ V cG(r d ,r)Φ x (r, r) s )ημ af (r)dV (11 Among them, G(r) d (r) represents the excitation light at position r propagating to position r. d The Green's function value corresponding to the time-diffusion equation, Φ x (r, r) s The excitation source is located at r s The density of excited photons propagating to point r, where η is the quantum efficiency, and μ af (r) represents the fluorescence absorption coefficient, c is the speed of light propagation in the tissue, and Φ m (r d r s ) is r d The detector at the location was detected by r s Fluorescence density excited by the light source.

[0111] To avoid inconvenience caused by different light sources and detectors in the calculation process, the normalized Born ratio method is used to reconstruct the fluorescence yield ημ. af That is, when the light source is located at r s r d When the detection location is determined, fluorescent photoflux is used. and excitation light photocurrent The normalized Born ratio Γ is obtained by comparing the measured values. nb (r d r s Using Robin's boundary conditions and Fick's law, we can obtain formula (2):

[0112] Γ(r d r s )=cΦ(r d r s ) / (2K) (2)

[0113] Where, Γ(r) d r s ) represents the boundary optical flux, Φ(r) d r s Let K be the optical density, and K = (1 + R) / (1 + R) f ) / (1-R f ), R f Let be the total reflection constant at the air-tissue boundary.

[0114] The measured value Γ of emitted fluorescence obtained by applying the forward model m(F) (r d r s ) and excitation light measurement value Γ x (F) (r d r s ), then Γ nb (r d r s ) can be expressed as formula (3).

[0115]

[0116] Where, r m (r d r s ) represents the boundary optical flux at the fluorescence wavelength, Γ x (r d r s ) is the boundary optical flux at the excitation wavelength, Φ x (r d r s The excitation light density is the source located at r. s The receiver at r d The excitation light density at the diffusion equation.

[0117] Based on the finite element method (FEM), formula (1) is discretized into individual parted volume elements, let Where u(r) is a shape function vector, and x(r) = [x1(r), x2(r), ..., x N (r)] T After discretization, it can be expressed as formula (4):

[0118] Φ m (r)=W(r)x(r) (4)

[0119] Where, Φ m W(r) is the photon density at voxel r, W(r) is the system matrix, and x(r) is the fluorescence absorption coefficient of voxel r.

[0120] Φ in formula (4) m w(r) can be calculated according to formula (5), and w(r) in formula (4) can be calculated according to formula (6).

[0121]

[0122]

[0123] Where N is the number of volume elements in the finite element method, and D and S are the number of detectors and sources, respectively. The elements W(r) of the system matrix W(r) i rj n1 can be calculated using formula (7).

[0124] W(r i r j ,n)=cG m (r i r n )Φ x (r n r j )ΔV (7)

[0125] Where n = 1, ... N; i = 1, ... D; j = 1, ... s, G m (r i r n ) and Φ x (r n r j ) are the G values ​​of each small volume element. m (r i ,r) and Φ x (r, r) j ) at the center r n The value at point G. m (r i , r) is the Green's function at the fluorescence wavelength, Φ x (r, r) j () is the excitation light density.

[0126] The Φ obtained based on the ART reconstruction method and formulas (4) to (7) m (r) and W(r), the fluorescence yield x calculated iteratively at the (k+1)th iteration. k+1 (r) is shown in expression (8).

[0127]

[0128] Among them, W (k) (r) is the k-th row of W(r), It is Φ m The k-th element of (r) is a relaxation factor, λ.

[0129] Since the fluorescence yields of the target and background obtained from FDOT reconstruction differ significantly, the maximum inter-class variance method can be used to calculate the inter-class variance σ1 based on the fluorescence yield. 2 and within-class variance σ² 2 And select the optimal threshold (i.e., the target threshold) t such that κ = σ1 2 / (σ1 2 +σ2 2 The maximum value is obtained. Therefore, the segmented image S(r) can be obtained according to formula (9).

[0130]

[0131] Where yield(r) is the fluorescence value in the fluorescence yield image.

[0132] As shown in formula (9), the entire S(r) image is divided into "target region" and "background region". The "target region" (ROI) contains the feature points of interest, and these grid nodes are selected for DOT reconstruction. During DOT reconstruction, the "background region", which is unrelated to the feature points, is assigned background optical parameters and does not participate in DOT reconstruction.

[0133] After obtaining the segmented image S(r), DOT reconstruction imaging begins. During DOT reconstruction, the host module 160 can perform the following operations to process the time series of the segmented image and the surface diffuse light image corresponding to each wavelength using diffusion optical tomography, obtaining a time series of three-dimensional images showing the change of absorption coefficients corresponding to each wavelength relative to the initial pressurization time: Based on the segmented image, a target matrix is ​​obtained, wherein the value of the target matrix is ​​equal to the value of the segmented image at positions where the number of rows and columns are equal, and the value of the target matrix is ​​a first preset value at positions where the number of rows and columns are not equal. That is, the sensitivity matrix in the process of reconstructing the time series image of the change of absorption coefficient is corrected by the target matrix, retaining only the spatial voxel positions where the fluorescence yield is greater than the threshold; Based on the target matrix and the time series of the surface diffuse light image corresponding to each wavelength, a time series of three-dimensional images showing the change of absorption coefficients corresponding to each wavelength relative to the initial pressurization time is obtained.

[0134] For example, based on the target matrix, the time series of surface diffuse light images corresponding to each wavelength can be used to perform three-dimensional reconstruction of breast tissue, resulting in a time series of three-dimensional images showing the change of absorption coefficients corresponding to each wavelength relative to the initial pressurization time.

[0135] For example, the first preset value can be 0.

[0136] For example, the host module 160 can perform the following operation to process the time series of the segmented image and the surface diffuse light image corresponding to each wavelength using diffusion optical tomography, and obtain the time series of the three-dimensional image of the change of the absorption coefficient corresponding to each wavelength relative to the initial pressurization time.

[0137] The Newton-Raphson method is a linearization method widely used in DOT image reconstruction. The formula for the k-th Newton-Raphson iteration is shown in formula (10).

[0138]

[0139] Where Γ represents a column vector of length S×D formed by the experimentally measured boundary measurements, and F(μ a k ) represents the k-th absorption coefficient μ a k The column vector of length S×D formed by the positive computational quantities under the distribution, J(μ) a k ) represents the absorption coefficient μ of the kth generation. a k The relevant Jacobian matrix, δμ a Let be the perturbation of the absorption coefficient, and k be the iteration number. The perturbation of the absorption coefficient characterizes the change in the absorption coefficient.

[0140] Let X represent the perturbation of the absorption coefficient δμ a Formula (10) can be expressed as the matrix form in Formula (11).

[0141] I = JX (11)

[0142] Where I represents the difference between the measured boundary quantity and the forward calculation quantity, is a column vector of size S×D, J is a Jacobian matrix of size S×D rows and N columns, and N represents the number of discrete nodes.

[0143] Equations (10) and (11) can be solved using Algebraic Reconstruction Technique (ART), that is, for a given μ... a Calculate the Jacobian matrix J, and then determine δμ. a Then update the optical parameter μ a (k+1) The iteration continues until the termination condition is met. The iteration process can be represented by formula (12).

[0144]

[0145] Among them, I k It is the k-th element of column vector I. yes The k-th row of the matrix, λ is the relaxation factor.

[0146] Based on the prior information provided by FDOT, the background area is directly set as the background value without the need for DOT reconstruction. Therefore, formula (12) can be simplified to formula (13).

[0147]

[0148] Where U is the target matrix and J(k) is the k-th Jacobian matrix, we arrange the columns corresponding to the target regions in SS(r) into matrix J in order. (k)The first NR columns, where NR represents the number of nodes within the target area. Let I be the Jacobian correction matrix for the k-th iteration. (k) For the k-th difference, Let X be the computational cost of the perturbation of the k-th absorption coefficient. (k) Let x be the perturbation of the k-th absorption coefficient. (k+1) It is the perturbation of the (k+1)th absorption coefficient.

[0149] The calculation method of the target matrix U in formula (13) is shown in formula (14).

[0150]

[0151] Where u(m) i n j Let ) be the target matrix U at the m-th... i Line n j The column value, S(i), represents the value corresponding to the position with a value of 1 in matrix S(r), where i ranges from 1 to NR.

[0152] From formula (14), we can see that and Only the values ​​at NR nodes need to be calculated. Obviously, the number of unknowns in DOT reconstruction is significantly reduced, which helps to alleviate the underdeterminacy of DOT reconstruction.

[0153] According to embodiments of this disclosure, the detection process using the fluorescence image-guided dynamic optical tomography system 100 for breast cancer provided in this disclosure is as follows:

[0154] Before the formal measurement, a pre-test is first performed, and the size range of the tissue to be measured is determined by the positioning light;

[0155] FDOT measurement was performed: the tissue to be tested was placed on the lamp plate of the first lifting platform, and the light source was configured to illuminate the 775nm wavelength light source for FDOT measurement; then a certain amount of ICG solution was injected into the tissue to be tested, and FDOT fluorescence was measured; a three-dimensional image of the fluorescence yield distribution inside the tissue was reconstructed, and the region of interest was extracted from the reconstructed image to obtain a segmented image.

[0156] DOT measurement is performed as follows: After placing the tissue to be measured on the lamp plate, the main module controls the second lifting platform to lower the pressure plate. The pressure stops when the set threshold is reached. At this point, the detection module begins to acquire and save surface diffuse light images, obtaining a time series of surface diffuse light images. After demodulating the time series of surface diffuse light images, DOT reconstruction is guided by the segmented images obtained from FDOT, reducing the underdeterminacy and ill-conditioned nature of the DOT inverse problem, and simultaneously achieving dynamic, high-quality imaging of breast tissue using diffuse optical tomography.

[0157] According to the fluorescence image-guided dynamic optical tomography system and detection process for breast tissue provided in this disclosure, when the target tissue is breast tissue, and the breast is compressed and fully parallel excited by a triangular LED array, the time series of the emitted light intensity image obtained by the incident light penetrating the breast tissue is acquired at high speed by the detection module. This can effectively improve data acquisition efficiency and measurement signal-to-noise ratio. The host module performs fully parallel demodulation of the emitted light intensity signal to obtain the corresponding light intensity change information. Relying on the high sensitivity of FDOT, the tumor lesion area is located from the fluorescence yield image reconstructed by FDOT. This can provide accurate prior location information for DOT reconstruction. Based on the initial pressure time, the DOT is guided to complete dynamic reconstruction, improving the quantification accuracy of DOT, increasing the reliability of DOT in assisting the early diagnosis of breast tumors, and promoting the application of diffusion optical tomography technology in the field of clinical breast lesion screening.

[0158] Those skilled in the art will understand that the features described in the various embodiments of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments of this disclosure can be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0159] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended embodiments and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A dynamic optical tomography system for breast imaging based on fluorescence image guidance, comprising: The first lifting platform is used to adjust the height of the light source module and the detection module, wherein the light source module and the detection module are located on both sides of the tissue to be detected, and the tissue to be detected includes mammary glands; The second lifting platform is used to control the movement of the pressure plate. The pressure plate is fixed on one side to the second lifting platform, and the other side is used to compress the tissue to be tested; The light source module is used to generate probe light of different wavelengths and positions under different frequency modulations, wherein the probe light includes a second probe light and a third probe light; The detection module is used to sample the emitted light of the second detection light after passing through the tissue to be detected to obtain a fluorescence reference image; after the tissue to be detected is combined with a fluorescent agent, the fluorescence emitted from the tissue to be detected after the second detection light passes through the tissue to be detected is sampled to obtain a surface fluorescence image; when the pressure of the pressure plate pressing the tissue to be detected reaches a preset pressure, the emitted light of the third detection light after passing through the tissue to be detected is sampled to obtain a time series of surface diffuse light images; The host module is used to process the fluorescence reference image and the surface fluorescence image using fluorescence diffusion optical tomography to obtain a three-dimensional image of the fluorescence yield distribution inside the tissue and to segment it to obtain a segmented image; to demodulate the time series of the surface diffuse light image to obtain the time series of the surface diffuse light image corresponding to each wavelength, including: performing a time-varying Fourier transform on each pixel in the surface diffuse light image to separate the spectral components at different modulation frequencies, the amplitude of these spectral components corresponding to the intensity of the light source at different modulation frequencies; filtering these spectral components obtained by the Fourier transform to retain the fundamental frequency and third harmonic components of each modulation frequency; performing an inverse Fourier transform on the filtered components to reconstruct the light intensity information; and using diffusion optical tomography to process the segmented image and the time series of the surface diffuse light image corresponding to each wavelength to obtain a time series of a three-dimensional image showing the change of the absorption coefficient corresponding to each wavelength relative to the initial pressurization time.

2. The system according to claim 1, wherein, The host module performs the following operations to process the time series of the segmented image and the surface diffuse light image corresponding to each wavelength using diffusion optical tomography, thereby obtaining a time series of three-dimensional images showing the change of absorption coefficients corresponding to each wavelength relative to the initial pressurization time: Based on the segmented image, a target matrix is ​​obtained, wherein at positions where the number of rows and columns are equal, the value of the target matrix is ​​equal to the value of the segmented image, and at positions where the number of rows and columns are not equal, the value of the target matrix is ​​a first preset value; Based on the target matrix and the time series of the surface diffuse light images corresponding to each wavelength, a time series of three-dimensional images of the changes in absorption coefficients corresponding to each wavelength relative to the initial pressurization time is obtained.

3. The system according to claim 2, wherein, The first preset value is 0.

4. The system according to any one of claims 1 to 3, wherein, The host module performs the following operations to process the surface fluorescence image using the fluorescence diffusion optical tomography method, obtain a three-dimensional image of the fluorescence yield distribution inside the tissue, and segment it to obtain a segmented image: The surface fluorescence image was processed using fluorescence diffusion optical tomography to obtain a three-dimensional image of the fluorescence yield distribution inside the tissue. Using the maximum inter-class variance method, based on the three-dimensional image of the fluorescence yield distribution within the tissue, the preset threshold inter-class variance and intra-class variance are calculated to obtain the target threshold; Based on the target threshold, the region of interest is extracted from the three-dimensional image of the fluorescence yield distribution within the tissue to obtain the segmented image.

5. The system according to claim 4, wherein, The light source module includes: The lower-level control unit is used to receive control commands issued by the host module and communicate with the LED driver unit through a preset communication mechanism to send the control commands to the LED driver unit. The light-emitting diode driving unit is used to generate driving signals according to the control command; The light-emitting diode lamp board unit is used to generate probe light modulated at different frequencies according to the driving signal.

6. The system according to claim 5, wherein, The LED light board unit includes: a light board, a positioning light, and a detection light; The positioning lights are arranged on circles of different radii with the bottom center of the light panel as the center, and the detection lights are arranged between the positioning lights and the bottom of the light panel, and the detection lights are arranged in a triangular pattern on the light panel. The detection light includes a first detection light emitted when both the positioning light and the detection light are driven to emit light, and the emitted image also includes a positioning image; The detection module performs the following operation to sample the emitted light after the detection light passes through the tissue to be detected, and obtain emitted light images of each wavelength corresponding to the emitted light intensity signal: The positioning image is obtained by sampling the emitted light after the first probe light passes through the tissue to be detected; The host module is also used to determine the size of the area of ​​the tissue to be detected based on the positioning image.

7. The system according to claim 6, wherein, Also includes: The pressure measurement module is used to monitor the pressure when the pressure plate compresses the tissue to be tested, and upload the signal corresponding to the pressure to the host module; The host module is also used to display the signal corresponding to the pressure in real time.

8. The system according to claim 7, wherein, The pressure measurement module includes: A pressure sensor is disposed between the tissue to be detected and the lamp panel for collecting pressure signals; The transmitter is used to convert the pressure signal into a weight signal and upload the weight signal to the host unit.

Images