Fluorescence camera system of medical endoscope

Abstract

The invention is suitable for the technical field of human body examination, and provides a medical endoscope fluorescence camera system, which comprises a fluorescent dye injection unit used for guiding a fluorescent dye to a target area, and the fluorescent dye generates a specific fluorescence signal in lesion tissues in the target area, the fluorescent dye is a chemical substance with target area lesion recognition capability, and the fluorescent dye generates a fluorescent signal capable of emitting a specific wavelength under irradiation of specific exciting light under metabolism or biological reaction of a target area so as to detect canceration characteristics; an endoscope imaging unit; according to the system, through adaptive partition threshold segmentation of the signal intensity analysis unit, image definition analysis and an Otsu method, the segmentation problem of the fluorescence image in different regions is effectively solved, and the recognition precision of the lesion region is improved. The display device is combined with a graphical user interface to provide visual operation, a doctor is helped to analyze the lesion in real time, and the aim of improving the lesion diagnosis accuracy and efficiency of a target area is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of target area inspection of lesions, and more specifically, to a medical endoscope fluorescence camera system. Background Art

[0002] At present, with the development of medical imaging technology in the market, endoscopic fluorescence camera technology, as an important diagnostic tool, is widely used in the early detection and evaluation of lesions in the target area. Endoscopic fluorescence camera uses fluorescent dyes to stimulate fluorescent signals in the lesion tissue under the irradiation of a specific excitation light source, and then converts the fluorescent signals into images through image acquisition equipment, helping doctors to observe and analyze the specific conditions of lesions in the target area in real time, such as gastric ulcers, gastritis, nasal cavity, uterine cavity and other parts where mucosa may be produced. This technology has become an important auxiliary tool for clinical diagnosis of lesions in the target area due to its non-invasive, real-time and high efficiency. Through the endoscopic camera system, doctors can more clearly identify the lesion area, evaluate its nature and monitor the progression of the lesion.

[0003] Although the existing endoscopic fluorescence camera system has achieved certain success in diagnosis, it still has certain limitations in image processing and segmentation of lesion areas. The existing technology mainly relies on traditional threshold segmentation methods, but these methods often cannot accurately process fluorescence images in areas of different clarity. For example, due to poor image quality or uneven illumination in some areas, image details may be lost or noise may interfere, resulting in unsatisfactory segmentation effects. Common threshold segmentation methods usually use the same threshold for the entire image, while ignoring the clarity differences in different areas. This one-size-fits-all processing method is difficult to meet the diversity and complexity of lesion images in the target area. In addition, the existing technology often uses fixed thresholds or simple image enhancement algorithms for processing unclear areas, lacking an effective adaptive mechanism to cope with the different features of different areas, thereby affecting the accuracy and robustness of the segmentation results.

[0004] Therefore, in view of the above problems, the present invention proposes a medical endoscope fluorescence imaging system. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention aims to provide a medical endoscope fluorescence imaging system.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] Medical endoscope fluorescence camera system, including:

[0008] A fluorescent dye injection unit, used to guide the fluorescent dye to the target area, the fluorescent dye generates a specific fluorescent signal in the target area lesion tissue, wherein the fluorescent dye is a chemical substance with the ability to identify the lesion in the target area, and the fluorescent dye generates a fluorescent signal of a specific wavelength under the irradiation of a specific excitation light under the metabolism or biological reaction of the target area, so as to detect the characteristics of canceration;

[0009] An endoscope camera unit, comprising a fluorescence excitation light source and an image acquisition device, wherein the fluorescence excitation light source is used to irradiate a target area with light of a suitable wavelength, thereby exciting the fluorescent dye to generate a fluorescence signal, and the image acquisition device is used to capture the fluorescence signal of the target area and convert the signal into a digital image, wherein the digital image reflects the characteristics of the lesion area of ​​the target area, including the type, location, size, and morphology of the lesion;

[0010] An image processing unit is used to process image data, improve image quality and enhance the contrast of the lesion area, identify and locate the lesion area based on threshold segmentation, and thus display the fluorescent image of the lesion area in the target area in real time;

[0011] A display device, used to receive the image processed by the image processing unit and display the processed fluorescence image to the doctor. The display device is a computer screen, through which the doctor can view the specific location, size and severity of the lesion in the target area in real time;

[0012] The patient information management module receives data information from the image processing unit and automatically records relevant information of the patient, such as name, age, medical history, and fluorescent images, so that doctors can conduct comprehensive analysis and long-term tracking to ensure the accuracy of diagnosis and continuity of treatment.

[0013] The present invention is further configured as follows: the fluorescent dye is aminolevulinic acid, which can be metabolized in the diseased tissue of the target area and generate a fluorescent signal of a specific wavelength under the excitation of a specific light source, thereby improving the visibility of the lesions in the target area.

[0014] The present invention is further configured as follows: the fluorescence excitation light source of the endoscope camera unit is an ultraviolet light source, a blue light source, a red-violet light source or a near-infrared light source, which is used in conjunction with ordinary white light. The excitation light source can excite the fluorescent dye to emit a fluorescent signal, and the wavelength range of the excitation light source is between 200nm and 820nm.

[0015] The present invention is further configured as follows: the image processing unit includes a signal strength analysis unit, a spatial distribution analysis unit, an image visualization unit, and a data storage and export unit;

[0016] Wherein, the signal intensity analysis unit is used to analyze the gray value distribution of pixels in the fluorescent image and adopt an adaptive segmentation method according to the clarity of different areas;

[0017] The spatial distribution analysis unit is used to calibrate and analyze the spatial characteristics of the segmented fluorescence signal area;

[0018] The image visualization unit is used to intuitively display the processed images and analysis results to medical personnel;

[0019] The data storage and export unit is used to store processed image data and analysis results, and provides data management and export functions.

[0020] The present invention is further configured as follows: the signal strength analysis unit adopts a partition threshold segmentation method in combination with the image clarity, and adopts different threshold segmentation strategies for the clear area and the unclear area of ​​the image, specifically including:

[0021] Segmentation of clear areas:

[0022] In the clear area, a fixed gray value threshold T is used fixed To split, the split formula is:

[0023]

[0024] Among them, g(x,y) is the gray value of pixel (x,y), T fixed is the preset threshold;

[0025] Unclear area segmentation:

[0026] In unclear areas, the Otsu method is used to automatically calculate the optimal threshold and segment by maximizing the inter-class variance. The calculation formula for the inter-class variance is:

[0027]

[0028] in, and are the weights of the two types of pixels respectively;

[0029] and are the average gray values ​​of the two types of pixels, respectively, where gi is the i-th gray value in the graph; p(gi) is the probability of occurrence of gray value gi;

[0030] is the inter-class variance, which is used to quantify the difference in grayscale values ​​between the two classes after segmentation.

[0031] The present invention is further configured as follows: a judgment unit is used to judge whether the image is a clear area or an unclear area, and the judgment unit is used to judge the clear area and the unclear area in the image according to the gray value distribution of each pixel in the fluorescent image and the contrast difference of the local area, and the judgment condition is:

[0032] Judgment of clear area:

[0033] The area with uniform grayscale distribution and high local contrast is judged as a clear area; the grayscale value of this area changes little and the local contrast of the pixel exceeds the preset contrast threshold;

[0034] Judgment of unclear areas:

[0035] An area with uneven grayscale distribution or low local contrast is judged as an unclear area; the grayscale value of this area varies greatly and the local contrast is less than the preset contrast threshold.

[0036] By adopting the above technical solution, the signal intensity analysis unit adopts a partition threshold segmentation method by combining image clarity, and adopts different threshold segmentation strategies for clear areas and unclear areas, which has significant advantages. First, for clear areas, the unit uses a fixed gray value threshold for segmentation, which ensures the efficiency and stability of image processing, and can accurately segment the lesion information of clear areas. For unclear areas, the Otsu adaptive threshold method is adopted to segment by maximizing the inter-class variance, making the processing of the area more flexible and accurate, and will not cause segmentation errors due to image blur. Through this strategy, the signal intensity analysis unit can adapt to the characteristics of different image areas, effectively improving the segmentation accuracy and robustness of the fluorescence image. In addition, the segmentation method that distinguishes between clear and unclear areas enables image processing to adopt the most appropriate strategy for different image qualities, thereby improving the diagnostic reliability of the overall system. In summary, the advantage of the signal intensity analysis unit is that it can automatically select the appropriate segmentation method under complex image conditions, greatly improving the accuracy and efficiency of fluorescence image processing.

[0037] The present invention is further configured as follows: the spatial distribution analysis unit comprises:

[0038] A region marking module is used to number the segmented fluorescence signal regions and mark their shapes and boundaries;

[0039] A position calibration module, used to determine the position of the fluorescent signal area in combination with the anatomical structure of the target area;

[0040] The geometric feature analysis module is used to calculate the area, perimeter, circularity, aspect ratio and other parameters of each fluorescent signal area to evaluate the morphological characteristics of the lesions.

[0041] The present invention is further configured as follows: the image visualization unit comprises:

[0042] A pseudo-color display module is used to superimpose the fluorescent signal on the anatomical image of the target area in pseudo-color form to facilitate observation by medical staff;

[0043] A dynamic display module is used to support the real-time display of the dynamic process of fluorescence signal changes;

[0044] The statistical information overlay module is used to overlay the fluorescence intensity value, area and other analysis parameters of the lesion area on the image.

[0045] The present invention is further configured as follows: the data storage and export unit comprises:

[0046] A data classification storage module is used to classify and store images and related data according to patient information and examination time;

[0047] Historical data retrieval module, used to quickly retrieve and call stored images and analysis results;

[0048] Multi-format export module supports exporting images and data in DICOM, JPEG or CSV formats for diagnostic reporting or further analysis.

[0049] The present invention is further configured as follows: the display device includes a graphical user interface, which allows doctors to view the fluorescent image of the lesion in the target area in real time, and can perform operations such as zooming, rotating, and marking, thereby helping doctors to analyze and diagnose the type and degree of gastric ulcer and gastritis in detail.

[0050] In summary, the present application includes at least one of the following beneficial technical effects:

[0051] 1. The signal intensity analysis unit adopts a partition threshold segmentation method by combining image clarity, and adopts different threshold segmentation strategies for clear areas and unclear areas, which has significant advantages. First, for clear areas, the unit uses a fixed gray value threshold for segmentation, which ensures the efficiency and stability of image processing, and can accurately segment the lesion information of clear areas. For unclear areas, the Otsu adaptive threshold method is used to segment by maximizing the inter-class variance, making the processing of this area more flexible and accurate, and will not cause segmentation errors due to image blur. Through this strategy, the signal intensity analysis unit can adapt to the characteristics of different image areas, effectively improving the segmentation accuracy and robustness of the fluorescence image. In addition, the segmentation method that distinguishes between clear and unclear areas enables image processing to adopt the most appropriate strategy for different image qualities, thereby improving the diagnostic reliability of the overall system. In summary, the advantage of the signal intensity analysis unit is that it can automatically select the appropriate segmentation method under complex image conditions, greatly improving the accuracy and efficiency of fluorescence image processing.

[0052] 2. The display device plays an important role in the target area fluorescence camera system. Through the graphical interface, doctors can view the processed target area fluorescence image in real time, clearly showing the location, morphology and severity of the lesion area. The interface supports operations such as zooming and rotating, and doctors can flexibly adjust the viewing angle to facilitate detailed analysis of the image. The annotation function can also help doctors mark the lesion area for further diagnosis and subsequent treatment decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a module schematic diagram of the medical endoscope fluorescence camera system of the present invention. DETAILED DESCRIPTION

[0054] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0055] It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meanings as commonly understood by ordinary technicians in the technical field to which this application belongs.

[0056] See also Figure 1 , the present invention provides the following technical solutions:

[0057] For example, see Figure 1 , a medical endoscope fluorescence camera system, comprising:

[0058] A fluorescent dye injection unit is used to guide the fluorescent dye to the target area, and the fluorescent dye generates a specific fluorescent signal in the lesion tissue in the target area, wherein the fluorescent dye is a chemical substance with the ability to identify the lesion in the target area, and the fluorescent dye generates a fluorescent signal of a specific wavelength under the irradiation of a specific excitation light under the metabolism or biological reaction of the target area, so as to detect the characteristics of canceration;

[0059] The endoscope camera unit includes a fluorescence excitation light source and an image acquisition device. The fluorescence excitation light source is used to irradiate the target area with light of a suitable wavelength, thereby exciting the fluorescent dye to generate a fluorescence signal. The image acquisition device is used to capture the fluorescence signal of the target area and convert the signal into a digital image. The digital image reflects the characteristics of the lesion area in the target area, including the type, location, size, and morphology of the lesion.

[0060] An image processing unit is used to process image data, improve image quality and enhance the contrast of the lesion area, identify and locate the lesion area based on threshold segmentation, and thus display the fluorescent image of the lesion area of ​​the target area in real time. The lesion area includes the stomach, nasal cavity, uterine cavity, etc. After the lesion, the lesion site can be combined with the fluorescent dye;

[0061] A display device, used to receive the image processed by the image processing unit and display the processed fluorescence image to the doctor. The display device is a computer screen, through which the doctor can view the specific location, size and severity of the lesion in the target area in real time;

[0062] The patient information management module receives data information from the image processing unit and automatically records the patient's relevant information, such as name, age, medical history, and fluorescent images, so that doctors can conduct comprehensive analysis and long-term tracking to ensure the accuracy of diagnosis and continuity of treatment.

[0063] The fluorescent dye is aminolevulinic acid, which can be metabolized in the diseased tissue of the target area and generate a fluorescent signal of a specific wavelength under the excitation of a specific light source, thereby improving the visibility of the lesions in the target area.

[0064] The fluorescence excitation light source of the endoscope camera unit is an ultraviolet light source, a blue light source, a red-violet light source or a near-infrared light source, which is used in conjunction with ordinary white light. For example, when the fluorescence excitation light source is not turned on, only ordinary white light is used. When necessary, the fluorescence excitation light source is turned on, and ordinary white light also works at the same time. The excitation light source can excite the fluorescent dye to emit a fluorescent signal, and the wavelength range of the excitation light source is between 200nm and 500nm. In addition, red-violet light with a wavelength range of 770-820nm or near-infrared excitation light sources can also be used to target lesion areas that are sensitive to different colors of fluorescence.

[0065] The image processing unit includes a signal strength analysis unit, a spatial distribution analysis unit, an image visualization unit, and a data storage and export unit;

[0066] The signal intensity analysis unit is used to analyze the gray value distribution of pixels in the fluorescent image and adopt an adaptive segmentation method according to the clarity of different areas;

[0067] The spatial distribution analysis unit is used to calibrate and analyze the spatial characteristics of the segmented fluorescence signal area;

[0068] The image visualization unit is used to intuitively display the processed images and analysis results to medical personnel;

[0069] The data storage and export unit is used to store processed image data and analysis results, and provides data management and export functions.

[0070] The signal strength analysis unit uses a partition threshold segmentation method in combination with the image clarity, and uses different threshold segmentation strategies for the clear and unclear areas of the image. Specifically, the signal strength analysis unit first divides the image into regions to distinguish between clear and unclear areas, and then selects an appropriate threshold segmentation strategy based on the characteristics of different regions. Specifically, it includes:

[0071] Segmentation of clear areas:

[0072] In the clear area, a fixed gray value threshold T is used fixed To split, the splitting formula is:

[0073]

[0074] Among them, g(x,y) is the gray value of pixel (x,y), T fixed is the preset threshold;

[0075] Unclear area segmentation:

[0076] In unclear areas, the Otsu method is used to automatically calculate the optimal threshold and segment by maximizing the inter-class variance. The calculation formula for the inter-class variance is:

[0077]

[0078] in, and are the weights of the two types of pixels respectively;

[0079] and are the average grayscale values ​​of the two types of pixels respectively; gi is the i-th grayscale level (grayscale value) in the image; p(gi) is the probability of occurrence of grayscale value gi, that is, the frequency or weight of the pixel corresponding to grayscale value gi, which indicates the proportion of this grayscale value in the image.

[0080] is the inter-class variance, which is used to quantify the difference in grayscale values ​​between the two classes after segmentation.

[0081] The image is a clear area or an unclear area using a judgment unit. The judgment unit is used to judge the clear area and the unclear area in the image according to the gray value distribution of each pixel in the fluorescent image and the contrast difference of the local area. The judgment conditions are:

[0082] Judgment of clear area:

[0083] The area with uniform grayscale distribution and high local contrast is judged as a clear area; the grayscale value of this area changes little and the local contrast of the pixel exceeds the preset contrast threshold;

[0084] Judgment of unclear areas:

[0085] An area with uneven grayscale distribution or low local contrast is judged as an unclear area; the grayscale value of this area varies greatly and the local contrast is less than the preset contrast threshold.

[0086] The spatial distribution analysis unit includes:

[0087] A region marking module is used to number the segmented fluorescence signal regions and mark their shapes and boundaries;

[0088] A position calibration module, used to determine the position of the fluorescent signal area in combination with the anatomical structure of the target area;

[0089] The geometric feature analysis module is used to calculate the area, perimeter, circularity, aspect ratio and other parameters of each fluorescent signal area to evaluate the morphological characteristics of the lesions.

[0090] The main function of the spatial distribution analysis unit is to perform spatial feature analysis on the segmentation results output by the signal intensity analysis unit. This includes calibration and spatial relationship analysis of the segmented fluorescence signal area. This unit further improves the accuracy of lesion area positioning by extracting features such as the geometric shape, position distribution, and size of the fluorescence area. The spatial distribution analysis unit can assist doctors in determining the precise range of the lesion area, help identify the extensibility and invasiveness of lesions in the target area, and provide further clinical decision support.

[0091] The image visualization unit includes:

[0092] A pseudo-color display module is used to superimpose the fluorescent signal on the anatomical image of the target area in pseudo-color form to facilitate observation by medical staff;

[0093] A dynamic display module is used to support the real-time display of the dynamic process of fluorescence signal changes;

[0094] The statistical information overlay module is used to overlay the fluorescence intensity value, area and other analysis parameters of the lesion area on the image.

[0095] The image visualization unit is used to clearly present the processed image data and analysis results to the doctor. The unit displays the segmented and analyzed fluorescence image and the spatial features of the lesion area in an intuitive way, including highlighting the lesion area in the image and marking its size, location and other features, so that the doctor can quickly locate and evaluate the lesion. In addition, the image visualization unit can also provide image zooming, rotation, contrast adjustment and other operation functions to help doctors view the target area lesion area more comprehensively from different angles.

[0096] The data storage and export unit includes:

[0097] A data classification storage module is used to classify and store images and related data according to patient information and examination time;

[0098] Historical data retrieval module, used to quickly retrieve and call stored images and analysis results;

[0099] Multi-format export module supports exporting images and data in DICOM, JPEG or CSV formats for diagnostic reporting or further analysis.

[0100] The task of the data storage and export unit is to store all processed fluorescence image data and related analysis results, and support the export function. This unit ensures that the patient's medical history data and diagnostic information can be preserved for a long time, which is convenient for subsequent follow-up and analysis. Doctors can easily export images of lesion areas, pathological analysis reports and other data through this unit for further clinical use or archiving. In addition, the data storage unit can also provide data sharing functions with other medical systems, promote the integration and sharing of medical data, and improve the efficiency of diagnosis and treatment.

[0101] The display device includes a graphical user interface that allows doctors to view fluorescent images of lesions in the target area in real time, and to perform operations such as zooming, rotating, and annotating, thereby helping doctors to analyze and diagnose the type and degree of gastric ulcers and gastritis in detail.

[0102] The display device plays a vital role in the target area fluorescence camera system. It is responsible for intuitively presenting the processed fluorescence images and analysis results to medical staff. Through this device, doctors can view detailed images of lesions in the target area in real time and make accurate analysis and diagnosis based on the lesion characteristics in the image. The display device not only provides image display function, but also includes a powerful graphical user interface, which enables doctors to flexibly operate in different operation modes and conduct multi-dimensional analysis.

[0103] The graphical user interface is designed to provide an intuitive and easy-to-use operating experience, ensuring that doctors can quickly and efficiently obtain key information about lesions in the target area during the intense diagnosis and treatment process. The interface uses modern graphic display technology and has the following functions:

[0104] Real-time image display: Doctors can view the fluorescent image of the target area in real time. The image display content includes the precise location, size, morphology and other characteristics of the lesion area. The image will be updated according to real-time data to ensure that doctors always have the latest information on the lesion in the target area.

[0105] Image zoom and rotation: The interface provides convenient zoom and rotation functions. Doctors can zoom in, zoom out or rotate the fluorescence image as needed to view the local features of the lesion area in more detail. Through the zoom function, doctors can view the tiny details of the lesion area, such as the ulcer boundary, local infiltration of gastritis, etc., so as to make a more accurate diagnosis.

[0106] Image labeling and annotation: During the image display process, doctors can use the labeling tools on the interface to mark the lesion area, including marking the specific location of gastric ulcers, the distribution range of gastritis, etc. The labeling tool supports a variety of labeling forms, such as rectangular boxes, circular boxes, arrows, text labels, etc. Doctors can use these labels to annotate images for subsequent analysis or follow-up records.

[0107] Multi-level image comparison and overlay: Doctors can overlay traditional images and fluorescent images on the same interface for comparison, helping to intuitively identify the differences and connections between lesions. This function is achieved through transparency adjustment, and doctors can view the overlapping areas of different types of images at the same time, thereby obtaining more comprehensive lesion information.

[0108] Obviously, the above-described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

Claims

1. A medical endoscope fluorescence camera system, characterized in that: include: A fluorescent dye injection unit, used to guide the fluorescent dye to the target area, the fluorescent dye generates a specific fluorescent signal in the target area lesion tissue, wherein the fluorescent dye is a chemical substance with the ability to identify the lesion in the target area, and the fluorescent dye generates a fluorescent signal of a specific wavelength under the irradiation of a specific excitation light under the metabolism or biological reaction of the target area, so as to detect the characteristics of canceration; An endoscope camera unit, comprising a fluorescence excitation light source and an image acquisition device, wherein the fluorescence excitation light source is used to irradiate a target area with light of a suitable wavelength, thereby exciting the fluorescent dye to generate a fluorescence signal, and the image acquisition device is used to capture the fluorescence signal of the target area and convert the signal into a digital image, wherein the digital image reflects the characteristics of the lesion area of ​​the target area, including the type, location, size, and morphology of the lesion; An image processing unit is used to process image data, improve image quality and enhance the contrast of the lesion area, identify and locate the lesion area based on threshold segmentation, and thus display the fluorescent image of the lesion area in the target area in real time; A display device, used to receive the image processed by the image processing unit and display the processed fluorescence image to the doctor. The display device is a computer screen, through which the doctor can view the specific location, size and severity of the lesion in the target area in real time; The patient information management module receives data information from the image processing unit and automatically records relevant information of the patient, such as name, age, medical history, and fluorescent images, so that doctors can conduct comprehensive analysis and long-term tracking to ensure the accuracy of diagnosis and continuity of treatment.

2. The medical endoscope fluorescence imaging system according to claim 1, characterized in that: The fluorescent dye is aminolevulinic acid, which can be metabolized in the lesion tissue in the target area and generate a fluorescent signal of a specific wavelength under the excitation of a specific light source, thereby improving the visibility of the lesion in the target area.

3. The medical endoscope fluorescence imaging system according to claim 1, characterized in that: The fluorescence excitation light source of the endoscope camera unit is an ultraviolet light source, a blue light source, a red-violet light source or a near-infrared light source, which is used in conjunction with ordinary white light. The excitation light source can excite the fluorescent dye to emit a fluorescent signal, and the wavelength range of the excitation light source is between 200nm and 820nm.

4. The medical endoscope fluorescence imaging system according to claim 1, characterized in that: The image processing unit includes a signal strength analysis unit, a spatial distribution analysis unit, an image visualization unit, and a data storage and export unit; Wherein, the signal intensity analysis unit is used to analyze the gray value distribution of pixels in the fluorescent image and adopt an adaptive segmentation method according to the clarity of different areas; The spatial distribution analysis unit is used to calibrate and analyze the spatial characteristics of the segmented fluorescence signal area; The image visualization unit is used to intuitively display the processed images and analysis results to medical personnel; The data storage and export unit is used to store processed image data and analysis results, and provides data management and export functions.

5. The medical endoscope fluorescence imaging system according to claim 4, characterized in that: The signal strength analysis unit adopts a partition threshold segmentation method in combination with the image clarity, and adopts different threshold segmentation strategies for the clear area and unclear area of ​​the image, specifically including: Segmentation of clear areas: In the clear area, a fixed gray value threshold T is used fixed To split, the split formula is: Among them, g(x,y) is the gray value of pixel (x,y), T fixed is the preset threshold; Unclear area segmentation: In unclear areas, the Otsu method is used to automatically calculate the optimal threshold and segment by maximizing the inter-class variance. The calculation formula for the inter-class variance is: in, and are the weights of the two types of pixels respectively; and are the average gray values ​​of the two types of pixels, respectively, where gi is the i-th gray value in the graph; p(gi) is the probability of occurrence of gray value gi; is the between-class variance, which is used to quantify the difference in grayscale values ​​between the two classes after segmentation.

6. The medical endoscope fluorescence imaging system according to claim 5, characterized in that: The image is judged as a clear area or an unclear area by a judging unit, and the judging unit is used to judge the clear area and the unclear area in the image according to the gray value distribution of each pixel in the fluorescent image and the contrast difference of the local area. The judging conditions are: the judgment of the clear area: The area with uniform grayscale distribution and high local contrast is judged as a clear area; the grayscale value of this area changes little and the local contrast of the pixel exceeds the preset contrast threshold; Judgment of unclear areas: An area with uneven grayscale distribution or low local contrast is judged as an unclear area; the grayscale value of this area varies greatly and the local contrast is less than the preset contrast threshold.

7. The medical endoscope fluorescence imaging system according to claim 4, characterized in that: The spatial distribution analysis unit comprises: A region marking module is used to number the segmented fluorescence signal regions and mark their shapes and boundaries; A position calibration module, used to determine the position of the fluorescent signal area in combination with the anatomical structure of the target area; The geometric feature analysis module is used to calculate the area, perimeter, circularity, aspect ratio and other parameters of each fluorescent signal area to evaluate the morphological characteristics of the lesions.

8. The medical endoscope fluorescence imaging system according to claim 4, characterized in that: The image visualization unit comprises: A pseudo-color display module is used to superimpose the fluorescent signal on the anatomical image of the target area in pseudo-color form to facilitate observation by medical staff; A dynamic display module is used to support the real-time display of the dynamic process of fluorescence signal changes; The statistical information overlay module is used to overlay the fluorescence intensity value, area and other analysis parameters of the lesion area on the image.

9. The medical endoscope fluorescence imaging system according to claim 4, characterized in that: The data storage and export unit comprises: A data classification storage module is used to classify and store images and related data according to patient information and examination time; Historical data retrieval module, used to quickly retrieve and call stored images and analysis results; Multi-format export module supports exporting images and data in DICOM, JPEG or CSV formats for diagnostic reporting or further analysis.

10. The medical endoscope fluorescence imaging system according to claim 1, characterized in that: The display device includes a graphical user interface, which allows doctors to view the fluorescent image of the lesion in the target area in real time and perform operations such as zooming, rotating, and marking.

Images