Medical endoscope fluorescence imaging system

Abstract

The application 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 for guiding fluorescent dye to a target area, wherein the fluorescent dye generates specific fluorescent signals in the diseased tissue of the target area, the fluorescent dye is a chemical substance with target area lesion recognition capability, and the fluorescent dye generates fluorescent signals of specific wavelengths under specific excitation light irradiation under the metabolism or biological response of the target area, so as to detect canceration characteristics; the system further comprises an endoscope camera unit; the system effectively solves the segmentation problem of fluorescent images in different areas through adaptive partition threshold segmentation of a signal intensity analysis unit, image definition analysis and an Otsu method, and improves the recognition accuracy of the diseased area. A display device combines a graphical user interface to provide intuitive operation, helps doctors to analyze the lesion in real time, and achieves the purpose of improving the accuracy and efficiency of target area lesion diagnosis.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of target area examination of lesions, more particularly, it relates to a medical endoscope fluorescence imaging system. BACKGROUND

[0002] At present, with the development of medical imaging technology, endoscope fluorescence imaging technology as an important diagnostic tool is widely used in early detection and evaluation of target area lesions. Endoscope fluorescence imaging excites the fluorescence signal in the lesion tissue under the irradiation of a specific excitation light source, and then converts the fluorescence signal into an image through an image acquisition device, helping doctors to observe and analyze the specific situation of the target area lesion in real time, such as gastric ulcer, gastritis, nasal cavity, uterine cavity, etc. This technology has become an important auxiliary tool for clinical diagnosis of target area lesions due to its non-invasiveness, real-time and high efficiency. Through the endoscope imaging system, doctors can more clearly identify the lesion area, evaluate its nature and monitor the progression of the lesion.

[0003] Although the existing endoscope fluorescence imaging system has achieved certain success in diagnosis, it still has certain limitations in image processing and lesion area segmentation. The existing technology mainly relies on traditional threshold segmentation methods, but these methods often cannot accurately process fluorescence images of different clarity areas. For example, due to low image quality or uneven lighting in some areas, details of the image may be lost or disturbed by noise, resulting in unsatisfactory segmentation results. Common threshold segmentation methods usually use the same threshold for the entire image, ignoring the clarity differences of different areas. This one-size-fits-all approach cannot meet the diversity and complexity of target area lesion images. In addition, the existing technology often uses fixed thresholds or simple image enhancement algorithms for unclear areas, lacking effective adaptive mechanisms to deal with 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 application provides a medical endoscope fluorescence imaging system. SUMMARY

[0005] In view of the deficiencies of the prior art, the purpose of the present application is to provide a medical endoscope fluorescence imaging system.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] The medical endoscope fluorescence imaging system comprises:

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

[0009] An endoscope camera unit comprises a fluorescent excitation light source configured to excite the fluorescent dye to generate a fluorescent signal by irradiating the target area with light of a suitable wavelength, and an image acquisition device configured to capture the fluorescent signal of the target area and convert the signal into a digital image reflecting 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 configured 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 display a fluorescent image of the lesion area of the target area in real time.

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

[0012] A patient information management module is configured to receive data information from the image processing unit and automatically record relevant information of the patient, such as name, age, medical history, and fluorescent image, so as to facilitate the doctor to conduct comprehensive analysis and long-term tracking, and ensure the accuracy of diagnosis and the continuity of treatment.

[0013] The application further provides that the fluorescent dye is aminolevulinic acid, which can be metabolized in the lesion 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 lesion in the target area.

[0014] The application further provides that the fluorescent 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 combination with ordinary white light, and 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 200 nm and 820 nm.

[0015] The application further provides that the image processing unit comprises a signal intensity analysis unit, a spatial distribution analysis unit, an image visualization unit, and a data storage and export unit.

[0016] The signal intensity analysis unit is configured to analyze the gray value distribution of pixels in the fluorescence image and adopt adaptive segmentation methods according to the definition of different regions.

[0017] The spatial distribution analysis unit is configured to calibrate and analyze the spatial features of the segmented fluorescence signal region.

[0018] The image visualization unit is configured to visually display the processed image and analysis result to medical staff.

[0019] The data storage and export unit is configured to store the processed image data and analysis result and provide data management and export functions.

[0020] The signal intensity analysis unit is further configured to adopt a partition threshold segmentation method in combination with the definition of the image, and different threshold segmentation strategies are adopted for the clear region and the unclear region of the image, specifically including:

[0021] Segmentation of the clear region:

[0022] In the clear region, a fixed gray value threshold T fixed is adopted for segmentation, and the segmentation formula is:

[0023]

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

[0025] Segmentation of the unclear region:

[0026] In the unclear region, the Otsu method is adopted to automatically calculate the optimal threshold, and segmentation is performed by maximizing the inter-class variance, and the calculation formula of the inter-class variance is:

[0027]

[0028] wherein and are the weights of the two types of pixels;

[0029] and are the average gray values of the two types of pixels, wherein gi is the i-th gray value, and p(gi) is the probability of the occurrence of the gray value gi.

[0030] is the inter-class variance, which is used to quantify the difference between the two types of gray values after segmentation.

[0031] The application is further provided: the image is a clear area or an unclear area, and a judgment unit is used for judging 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 that:

[0032] Clear area judgment:

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

[0034] Unclear area judgment:

[0035] In the area with uneven gray value distribution or low local contrast, the area is judged as an unclear area; the gray value of the area changes greatly, and the local contrast is less than the preset contrast threshold.

[0036] By using the above technical solution, the signal intensity analysis unit combines the image clarity, uses the partition threshold segmentation method, adopts different threshold segmentation strategies for the clear area and the unclear area, and has obvious advantages. First, for the clear area, the unit uses a fixed gray value threshold for segmentation, ensuring the efficiency and stability of image processing, and can accurately segment the lesion information of the clear area. For the unclear area, the Otsu adaptive threshold method is used to maximize the inter-class variance for segmentation, so that the processing of the area is more flexible and accurate, and segmentation errors caused by image blur are avoided. 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 fluorescent image. In addition, the segmentation method of distinguishing clear and unclear areas enables the image processing to adopt the most appropriate strategy for different image quality, 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 fluorescent image processing.

[0037] The application is further provided: the spatial distribution analysis unit includes:

[0038] A region marking module is used for numbering the segmented fluorescent signal region and marking the shape and boundary thereof;

[0039] A position calibration module is used for determining the position of the fluorescent signal region in combination with the anatomical structure of the target area;

[0040] A geometric feature analysis module is used for calculating the area, perimeter, circularity and aspect ratio of each fluorescent signal region, and evaluating the morphological features of the lesion.

[0041] The application is further configured that the image visualization unit comprises:

[0042] A pseudo-color display module is configured to superimpose the fluorescence signal on the target region anatomical image in the form of pseudo-color for the medical staff to observe;

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

[0044] A statistical information superimposition module is configured to superimpose and display the fluorescence intensity value, area and other analysis parameters of the lesion region on the image.

[0045] The application is further configured that the data storage and export unit comprises:

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

[0047] A historical data retrieval module is configured to quickly retrieve and call the stored images and analysis results;

[0048] A multi-format export module is configured to support export of the images and data in DICOM, JPEG or CSV format for diagnostic report or further analysis.

[0049] The application is further configured that the display device comprises a graphical user interface, which allows the doctor to view the fluorescence image of the lesion in the target region in real time, and can perform zooming, rotating, labeling and other operations, thereby helping the doctor to analyze and diagnose the type and degree of gastric ulcer and gastritis in detail.

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

[0051] 1、Signal intensity analysis unit has the following advantages: first, for the clear area, the unit uses a fixed gray value threshold for segmentation, ensuring the efficiency and stability of image processing, and can accurately segment the lesion information of the clear area. For the unclear area, the Otsu adaptive threshold method is used to maximize the inter-class variance for segmentation, making the processing of this area more flexible and accurate, and not causing segmentation errors due to image blur. Through this strategy, the signal intensity analysis unit can adapt to the characteristics of different image regions, effectively improving the segmentation accuracy and robustness of the fluorescence image. In addition, the segmentation method of distinguishing clear and unclear areas enables the image processing to adopt the most appropriate strategy for different image quality, thereby improving the diagnostic reliability of the overall system. In summary, the signal intensity analysis unit has the advantage of automatically selecting the appropriate segmentation method under complex image conditions, greatly improving the accuracy and efficiency of fluorescence image processing.

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

[0053] Figure 1 Figure 1 is a schematic diagram of the medical endoscope fluorescence imaging system of the present application. DETAILED DESCRIPTION

[0054] It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0055] It should be noted that, unless otherwise specified, all technical and scientific terms used in the present application have the same meaning as generally understood by those skilled in the art to which the present application belongs.

[0056] Please refer to Figure 1 The present application provides the following technical solutions:

[0057] Embodiment one, please refer to Figure 1 The medical endoscope fluorescence imaging system comprises:

[0058] The 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 target area lesion tissue, wherein the fluorescent dye is a chemical substance with target area lesion recognition capability, and the fluorescent dye generates a fluorescent signal of a specific wavelength under the excitation of a specific excitation light, so as to detect the characteristics of canceration.

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

[0060] The image processing unit is used to process image data, improve image quality, and enhance the contrast of the lesion area, and based on threshold segmentation, the lesion area is identified and located, so as to display the fluorescent image of the lesion area of the target area in real time, and the lesion area includes the stomach, nasal cavity, uterine cavity, and other lesions, and the lesion site can be combined with the fluorescent dye of the disease;

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

[0062] The patient information management module receives the data information of the image processing unit and automatically records the relevant information of the patient, such as name, age, medical history, and fluorescent image, so as to facilitate the doctor to make a comprehensive analysis and long-term tracking, and ensure the accuracy of diagnosis and the continuity of treatment.

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

[0064] The fluorescent 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 cooperation with ordinary white light, for example, when the fluorescent excitation light source is not turned on, only ordinary white light is used, and when needed, the fluorescent excitation light source is turned on, and the ordinary white light also works. 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 200 nm and 500 nm. In addition, a red-violet light source with a wavelength range of 770-820 nm or a near-infrared light source can also be used to target lesion areas sensitive to different colors of fluorescent light.

[0065] The image processing unit comprises a signal intensity 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 configured to analyze the gray value distribution of pixels in the fluorescence image and adopt adaptive segmentation methods according to the definition of different regions.

[0067] The spatial distribution analysis unit is configured to calibrate and analyze the spatial features of the segmented fluorescence signal region.

[0068] The image visualization unit is configured to visually display the processed image and analysis results to medical personnel.

[0069] The data storage and export unit is configured to store the processed image data and analysis results and provide data management and export functions.

[0070] The signal intensity analysis unit adopts a partition threshold segmentation method in combination with the definition of the image, and different threshold segmentation strategies are adopted for the clear and unclear regions of the image. Specifically, the signal intensity analysis unit first divides the image into clear and unclear regions, and then selects appropriate threshold segmentation strategies according to the characteristics of different regions. Specifically, the signal intensity analysis unit adopts the following threshold segmentation strategies:

[0071] Segmentation of clear regions:

[0072] In the clear region, a fixed gray value threshold T fixed is used for segmentation, and the segmentation formula is:

[0073]

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

[0075] Segmentation of unclear regions:

[0076] In the unclear region, the Otsu method is used to automatically calculate the optimal threshold value, and the segmentation is performed by maximizing the inter-class variance, and the calculation formula of the inter-class variance is:

[0077]

[0078] where w and w are the weights of the two types of pixels, respectively.

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

[0080] is the inter-class variance, which is used to quantify the difference between the two types of gray values after segmentation.

[0081] The image is judged 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, and the judging condition is:

[0082] Judgment of the clear area:

[0083] In the area where the gray value distribution is relatively uniform and the local contrast is high, it is judged as a clear area; the gray value of the area changes little, and the local contrast of the pixel exceeds the preset contrast threshold;

[0084] Judgment of the unclear area:

[0085] In the area where the gray value distribution is not uniform or the local contrast is low, it is judged as an unclear area; the gray value of the area changes greatly, and the local contrast is less than the preset contrast threshold.

[0086] The spatial distribution analysis unit includes:

[0087] The area marking module is used to number and mark the shape and boundary of the segmented fluorescent signal area;

[0088] The position calibration module is 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 and aspect ratio of each fluorescent signal area, which is used to evaluate the morphological characteristics of the lesion.

[0090] The main function of the spatial distribution analysis unit is to analyze the spatial features of the segmentation results output by the signal intensity analysis unit. This includes marking and spatial relationship analysis of the segmented fluorescent signal area. Through extracting the geometric shape, position distribution and size of the fluorescent area, the spatial distribution analysis unit further improves the accuracy of lesion area positioning. The spatial distribution analysis unit can assist doctors in determining the accurate range of the lesion area, helping to identify the expansibility and invasiveness of the target area lesion, and providing further clinical decision support.

[0091] The image visualization unit includes:

[0092] A pseudo-color display module is used to superimpose the fluorescence signal in pseudo-color form on the target area anatomical image, facilitating observation by medical personnel;

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

[0094] A statistical information superimposition module is used to superimpose and display 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. This unit displays the segmented and analyzed fluorescence image and the spatial features of the lesion area in an intuitive manner, including highlighting the lesion area on the image, labeling its size, position, and other features, to facilitate the doctor's rapid positioning and evaluation of the lesion condition. In addition, the image visualization unit can also provide image zooming, rotating, contrast adjustment, and other operation functions to help the doctor view the target area lesion area from different angles more comprehensively.

[0096] The data storage and export unit includes:

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

[0098] A historical data retrieval module is used to quickly retrieve and call stored images and analysis results;

[0099] A multi-format export module is used to support exporting images and data in DICOM, JPEG, or CSV format for diagnostic reports 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 export functions. This unit ensures that patient medical history data and diagnostic information can be stored for a long time, facilitating subsequent follow-up and analysis. Doctors can easily export lesion area images, 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, promoting the integration and sharing of medical data and improving diagnosis and treatment efficiency.

[0101] The display device includes a graphical user interface that allows doctors to view fluorescence images of target area lesions in real time and can perform zooming, rotating, labeling, and other operations to help doctors analyze and diagnose the type and extent of gastric ulcer and gastritis in detail.

[0102] The display device plays a crucial role in the target area fluorescence imaging system, which is responsible for presenting the processed fluorescence images and analysis results to medical personnel in a visual manner. Through this device, doctors can view detailed images of target area lesions in real time and make accurate analysis and diagnosis based on the lesion characteristics in the images. The display device not only provides image display functions, but also contains a powerful graphical user interface, allowing doctors to flexibly operate and perform multi-dimensional analysis in different operation modes.

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

[0104] Real-time image display: doctors can view real-time fluorescence images of the target area, and the image display content includes accurate positioning, size, shape, 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 about the target area lesions.

[0105] Image zooming and rotating: the interface provides convenient zooming and rotating functions, allowing doctors to enlarge, reduce, or rotate the fluorescence image as needed to view the local features of the lesion area in more detail. Through the zoom-in function, doctors can view the small details of the lesion area, such as ulcer borders, local infiltration of gastritis, etc., to make more accurate diagnoses.

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

[0107] Multi-level image comparison and superimposition: doctors can superimpose traditional images and fluorescence images on the same interface for comparison to help intuitively identify the differences and relationships between lesions. This function is achieved through transparency adjustment, allowing doctors to view the overlapping areas of different types of images simultaneously to obtain more comprehensive lesion information.

[0108] Obviously, the above-described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor should belong to the scope of protection of the present application.

Claims

1. A medical endoscope fluorescence imaging system, characterized by: The application relates to a fluorescence dye injection unit for guiding fluorescence dye to a target area, wherein the fluorescence dye is a chemical substance with target area lesion recognition capability, and the fluorescence dye generates a fluorescence signal of a specific wavelength under specific excitation light irradiation under metabolism or biological reaction of the target area, so as to detect canceration characteristics. An endoscope camera unit comprises a fluorescence excitation light source for exciting the fluorescence dye to generate a fluorescence signal by irradiating the target area with light of a suitable wavelength, and an image acquisition device for capturing the fluorescence signal of the target area and converting the signal into a digital image reflecting the characteristics of the lesion area of the target area, including the type, position, size and morphology of the lesion. An image processing unit is used for processing image data, improving image quality and enhancing the contrast of the lesion area, identifying and locating the lesion area based on threshold segmentation, so as to display a fluorescence image of the lesion area of the target area in real time. A display device is used for receiving the image processed by the image processing unit and displaying the processed fluorescence image to a doctor, and the display device is a computer screen, and the doctor can view the specific position, size and severity of the lesion of the target area in real time through the device. A patient information management module receives data information of the image processing unit, automatically records the relevant information of the patient, so as to facilitate the doctor to make comprehensive analysis and long-term tracking, and ensure the accuracy of diagnosis and the continuity of treatment. The image processing unit comprises a signal intensity analysis unit, a spatial distribution analysis unit, an image visualization unit and a data storage and export unit. The signal intensity analysis unit is used for analyzing the gray value distribution of pixels in the fluorescence image, and adopting adaptive segmentation methods according to the definition of different regions. The spatial distribution analysis unit is used for calibrating and analyzing the spatial characteristics of the segmented fluorescence signal region. The image visualization unit is used for visually displaying the processed image and analysis result to medical personnel. The data storage and export unit is used for storing the processed image data and analysis result, and providing data management and export functions. The signal intensity analysis unit adopts a partition threshold segmentation method in combination with image definition, different threshold segmentation strategies are adopted for clear regions and unclear regions of the image, and the clear region segmentation specifically comprises the following steps: The unclear region segmentation specifically comprises the following steps: In the unclear region, the best threshold is automatically calculated by adopting an Otsu method, and segmentation is carried out by maximizing the inter-class variance, and the calculation formula of the inter-class variance is as follows: In the clear area, a fixed gray value threshold is used Segmentation is performed with the formula: in, For pixels grayscale value, The preset threshold; The fluorescence dye is aminolevulinic acid, the fluorescence dye can be metabolized in the lesion tissue of the target area, and a fluorescence signal of a specific wavelength is generated under excitation of a specific light source, so as to improve the visibility of the lesion of the target area. ​ wherein 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; p(gi) is the probability of the occurrence of the gray value gi. is the inter-class variance, which is used to quantify the difference between the two classes of gray values after segmentation.

2. The medical endoscope fluorescence imaging system according to claim 1, characterized by: ​ 3. The medical endoscope fluorescence imaging system according to claim 1, characterized by: 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 cooperation with ordinary white light. The excitation light source can excite the fluorescent dye to emit a fluorescence signal, and the wavelength range of the excitation light source is between 200 nm and 820 nm.

4. The medical endoscope fluorescence imaging system according to claim 1, characterized by: The image is clear or unclear area judgment unit for judging, the judgment unit is used for judging the clear area and unclear area in the image according to the gray value distribution of each pixel in the fluorescence image and the contrast difference of local area, the judgment condition is: Clear area judgment: In the area with uniform gray value distribution and high local contrast, it is judged as a clear area; the gray value of this area changes little, and the local contrast of the pixel exceeds the preset contrast threshold; Unclear area judgment: In the area with uneven gray value distribution or low local contrast, it is judged as an unclear area; the gray value of this area changes greatly, and the local contrast is less than the preset contrast threshold.

5. The medical endoscope fluorescence imaging system according to claim 1, wherein: The spatial distribution analysis unit includes: Region marking module, for numbering the segmented fluorescent signal region, and marking its shape and boundary; Position calibration module, for determining the position of the fluorescent signal region in combination with the target region anatomical structure; Geometric feature analysis module, for calculating the area, perimeter, circularity and aspect ratio of each fluorescent signal region, for evaluating the lesion morphological characteristics.

6. The medical endoscope fluorescence imaging system according to claim 1, wherein: The image visualization unit includes: Pseudo-color display module, for superimposing the fluorescent signal on the target region anatomical image in the form of pseudo-color, facilitating medical personnel observation; Dynamic display module, for supporting real-time display of the dynamic process of fluorescent signal change; Statistical information superposition module, for superimposing and displaying the fluorescence intensity value, area and other analysis parameters of the lesion region on the image.

7. The medical endoscope fluorescence imaging system according to claim 1, characterized by: The data storage and export unit includes: Data classification storage module, for storing images and related data according to patient information and examination time; History data retrieval module, for quickly retrieving and calling stored images and analysis results; Multi-format export module, for supporting image and data export in DICOM, JPEG or CSV format for diagnostic report or further analysis.

8. The medical endoscope fluorescence imaging system according to claim 1, characterized by: The display device includes a graphical user interface that allows doctors to view the fluorescence image of the target region lesion in real time, and to zoom, rotate and label.

Images