An endoscopic image processing method based on blood oxygen saturation and multi-center wavelength

Abstract

This application discloses an endoscopic image processing method based on blood oxygen saturation and multi-center wavelength, relating to the field of medical image processing. The method includes acquiring a first initial image signal, a second initial image signal, a third initial image signal, and a fourth initial image signal; calculating oxyhemoglobin concentration information at a target site based on the second and third initial image signals; calculating deoxyhemoglobin concentration information at the target site based on the second and fourth initial image signals; calculating blood oxygen saturation at the target site based on the oxyhemoglobin and deoxyhemoglobin concentration information; enhancing the brightness of the second initial image signal based on the blood oxygen saturation to obtain a second enhanced image signal; and generating a target image based on the second enhanced image signal, the first initial image signal, and the third initial image signal. The target image is used to identify the bleeding location at the target site.

Description

Technical Field

[0001] This application relates to the field of medical image processing, and in particular to an endoscopic image processing method based on blood oxygen saturation and multi-center wavelength. Background Technology

[0002] In the medical field, gastrointestinal bleeding is a common acute and critical condition in internal medicine, frequently seen in cases of peptic ulcers, esophageal and gastric varices, and cancerous bleeding. Endoscopic treatment is an effective means of treating gastrointestinal bleeding. Timely assessment of the condition and rapid identification of the cause and location of bleeding can help doctors quickly stop the bleeding.

[0003] In existing technologies, hemoglobin concentration is generally used to distinguish bleeding points from other sites. Typically, the hemoglobin concentration is higher at the bleeding point. Although blood flows and spreads outwards, it is continuously diluted by other bodily fluids during this process, resulting in a lower hemoglobin concentration in the diluted blood. Thus, the bleeding point can be identified by hemoglobin concentration. However, when bleeding has been ongoing for some time, a large amount of coagulated or semi-coagulated blood forms in non-bleeding areas. The hemoglobin concentration in this coagulated or semi-coagulated blood is also very high, making it difficult to distinguish between the coagulated or semi-coagulated blood and the blood at the bleeding point using hemoglobin concentration alone, thus hindering accurate identification of the bleeding point. Summary of the Invention

[0004] The purpose of this application is to provide an endoscopic image processing method based on blood oxygen saturation and multi-center wavelength, which can generate target images that can simultaneously distinguish between blood at the bleeding point, coagulated or semi-coagulated blood, and diluted blood. This facilitates medical personnel in accurately determining the location of the bleeding point. Compared with existing technologies, this method further eliminates the interference of coagulated or semi-coagulated blood and solves the problem that existing endoscopic image processing methods have difficulty distinguishing between coagulated or semi-coagulated blood and blood at the bleeding point.

[0005] To achieve the above objectives, this application provides the following solution:

[0006] In a first aspect, this application provides an endoscopic image processing method based on blood oxygen saturation and multi-center wavelength, characterized in that the endoscopic image processing method includes:

[0007] Acquire a first initial image signal, a second initial image signal, a third initial image signal, and a fourth initial image signal; wherein the first initial image signal, the second initial image signal, the third initial image signal, and the fourth initial image signal are image signals obtained by irradiating the target area with light of a first band, a second band, a third band, and a fourth band, respectively, where the first band is 395nm-450nm, the second band is 444nm-636nm, the third band is 605nm-635nm, and the fourth band is 812.5nm-837.5nm;

[0008] The oxyhemoglobin concentration information of the target site is calculated based on the second initial image signal and the third initial image signal;

[0009] The deoxyhemoglobin concentration information of the target site is calculated based on the second initial image signal and the fourth initial image signal;

[0010] The oxygen saturation of the target site is calculated based on the oxyhemoglobin concentration information and the deoxyhemoglobin concentration information.

[0011] The second enhanced image signal is obtained by enhancing the brightness of the second initial image signal based on the blood oxygen saturation.

[0012] A target image is generated based on the second enhanced image signal, the first initial image signal, and the third initial image signal, and the target image is used to identify the bleeding location of the target site.

[0013] In a second aspect, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the endoscopic image processing method based on blood oxygen saturation and multi-center wavelength as described above.

[0014] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the endoscopic image processing method based on blood oxygen saturation and multi-center wavelength described above.

[0015] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the endoscopic image processing method based on blood oxygen saturation and multi-center wavelength as described above.

[0016] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0017] This application provides an endoscopic image processing method based on blood oxygen saturation and multi-center wavelength. Although coagulated or semi-coagulated blood and blood at the bleeding point have similar hemoglobin concentrations, the ratios of oxyhemoglobin and deoxyhemoglobin in the two types of blood differ significantly. Since blood oxygen saturation provides information on the ratio of oxyhemoglobin to deoxyhemoglobin, enhancing the brightness of the second initial image signal using this blood oxygen saturation can distinguish regions in the image with different ratios of oxyhemoglobin and deoxyhemoglobin, thereby obtaining a second enhanced image signal capable of differentiating between different types of blood. Simultaneously, blood at the bleeding point and diluted blood in the initial image signal can be distinguished based on hemoglobin concentration. Therefore, combining the second enhanced image signal, the first initial image signal, and the third initial image signal yields a target image capable of simultaneously distinguishing blood at the bleeding point, coagulated or semi-coagulated blood, and diluted blood. It should be noted that the target image is an RGB color image. To generate the target image, it is necessary to first acquire signals from three different channels. The band of the second enhanced image signal corresponds to the G channel signal, and the bands of the first initial image signal and the third initial image signal correspond to the B channel signal and the R channel signal, respectively. Therefore, the first initial image signal and the third initial image signal are combined with the second enhanced image signal to generate the target image. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is an application environment diagram of an endoscopic image processing method based on blood oxygen saturation and multi-center wavelength in one embodiment of this application;

[0020] Figure 2 A schematic flowchart of an endoscopic image processing method based on blood oxygen saturation and multi-center wavelengths provided in an embodiment of this application;

[0021] Figure 3 This is a data transfer diagram of an endoscopic image processing method based on blood oxygen saturation and multi-center wavelength, provided as an embodiment of this application. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] This application provides an endoscopic image processing method based on blood oxygen saturation and multi-center wavelengths, which can be applied to, for example... Figure 1 The application environment shown is illustrated. Terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be set up independently, integrated into server 102, or placed in the cloud or on another server. Terminal 101 can send a first initial image signal, a second initial image signal, a third initial image signal, and a fourth initial image signal to server 102. Upon receiving these signals, server 102 executes the following steps: calculating the oxyhemoglobin concentration information of the target site based on the second and third initial image signals; calculating the deoxyhemoglobin concentration information of the target site based on the second and fourth initial image signals; calculating the blood oxygen saturation of the target site based on the oxyhemoglobin and deoxyhemoglobin concentration information; enhancing the brightness of the second initial image signal based on the blood oxygen saturation to obtain a second enhanced image signal; and generating a target image based on the second enhanced image signal, the first initial image signal, and the third initial image signal. The target image is used to identify the bleeding location of the target site. Server 102 can then feed back the obtained bleeding location of the target site to terminal 101. In addition, in some embodiments, the endoscopic image processing method based on blood oxygen saturation and multi-center wavelength can also be implemented by the server 102 or the terminal 101 separately.

[0025] The terminal 101 can be, but is not limited to, various desktop computers, laptops, smartphones, and tablets. The server 102 can be implemented using a standalone server or a server cluster consisting of multiple servers, or it can be a cloud server.

[0026] In one exemplary embodiment, such as Figure 2 and Figure 3As shown, an endoscopic image processing method based on blood oxygen saturation and multi-center wavelengths is provided. This method is executed by a computer device, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps 210 to 260.

[0027] Step 210: Acquire a first initial image signal, a second initial image signal, a third initial image signal, and a fourth initial image signal; wherein, the first initial image signal, the second initial image signal, the third initial image signal, and the fourth initial image signal are image signals obtained by irradiating the target area with light of the first band, the second band, the third band, and the fourth band, respectively. The first band is 395nm-450nm, the second band is 444nm-636nm, the third band is 605nm-635nm, and the fourth band is 812.5nm-837.5nm.

[0028] Step 220: Calculate the oxyhemoglobin concentration information of the target site based on the second initial image signal and the third initial image signal.

[0029] Step 230: Calculate the deoxyhemoglobin concentration information of the target site based on the second initial image signal and the fourth initial image signal.

[0030] Step 240: Calculate the oxygen saturation of the target site based on the oxyhemoglobin concentration information and the deoxyhemoglobin concentration information.

[0031] Step 250: The second initial image signal is enhanced based on blood oxygen saturation to obtain the second enhanced image signal.

[0032] Step 260: Generate a target image based on the second enhanced image signal, the first initial image signal, and the third initial image signal. The target image is used to identify the bleeding location of the target site.

[0033] In this embodiment, the first band of light is narrowband blue light with a center wavelength of 430 nm and a half-width at half-maximum (HWHM) of 20 nm, or narrowband blue-violet light with a center wavelength of 415 nm and HWHM of 20 nm. The second band of light is broadband green light with a center wavelength of 540 nm and HWHM of 96 nm. The third band of light is narrowband red light with a center wavelength of 625 nm and HWHM of 20 nm. The fourth band of light is near-infrared light with a center wavelength of 825 nm and HWHM of 12.5 nm. All bands of light are emitted by light sources, and each light source can be an LED, or some light sources can be LEDs. For example, some bands of light are obtained by filtering a broadband light source through a filter.

[0034] In the second band, the absorbance coefficients of oxyhemoglobin and deoxyhemoglobin are similar. In the fourth band, the absorbance coefficient of oxyhemoglobin is higher than that of deoxyhemoglobin, resulting in a relatively higher reflectance intensity for deoxyhemoglobin. Therefore, the hemoglobin concentration calculated from the second and fourth initial image signals is mainly contributed by deoxyhemoglobin, thus providing deoxyhemoglobin concentration information. In the third band, the absorbance coefficient of deoxyhemoglobin is significantly higher than that of oxyhemoglobin, resulting in a significantly higher reflectance intensity for oxyhemoglobin. Therefore, the hemoglobin concentration calculated from the second and third initial image signals is mainly contributed by oxyhemoglobin, thus providing oxyhemoglobin concentration information. Furthermore, the oxygen saturation of the target site can be calculated based on the oxyhemoglobin and deoxyhemoglobin concentration information. Although coagulated or semi-coagulated blood and blood at the bleeding point have similar hemoglobin concentrations, the ratios of oxyhemoglobin and deoxyhemoglobin differ significantly between the two types of blood. Since blood oxygen saturation provides information on the ratio of oxyhemoglobin to deoxyhemoglobin, enhancing the brightness of the second initial image signal using blood oxygen saturation can distinguish regions in the image with different ratios of oxyhemoglobin and deoxyhemoglobin, thus obtaining a second enhanced image signal capable of differentiating between different types of blood (coagulated or semi-coagulated blood and blood at the bleeding point). Simultaneously, blood at the bleeding point and diluted blood in the initial image signal can be distinguished based on hemoglobin concentration (this can be achieved using existing techniques). Therefore, combining the second enhanced image signal, the first initial image signal, and the third initial image signal yields a target image capable of simultaneously distinguishing blood at the bleeding point, coagulated or semi-coagulated blood, and diluted blood. It should be noted that the target image is an RGB color image. To generate the target image, it is necessary to first acquire signals from three different channels. The band of the second enhanced image signal corresponds to the G channel signal, and the bands of the first initial image signal and the third initial image signal correspond to the B channel signal and the R channel signal, respectively. Therefore, the first initial image signal and the third initial image signal are combined with the second enhanced image signal to generate the target image.

[0035] In summary, by implementing steps 210 to 260, a target image can be generated that can simultaneously distinguish between blood at the bleeding point, coagulated or semi-coagulated blood, and diluted blood. This facilitates medical personnel in accurately determining the location of the bleeding point. Compared to existing technologies, this further eliminates interference from coagulated or semi-coagulated blood and solves the problem that existing endoscopic image processing methods have difficulty distinguishing between coagulated or semi-coagulated blood and blood at the bleeding point.

[0036] The following further describes the implementation details of the endoscopic image processing method based on blood oxygen saturation and multi-center wavelength in this embodiment.

[0037] The formula for calculating oxyhemoglobin concentration information is:

[0038]

[0039] in, This indicates information about oxyhemoglobin concentration. This represents the third initial image signal. Represents the second initial image signal

[0040] The formula for calculating deoxyhemoglobin concentration information is:

[0041]

[0042] in, This indicates information about deoxyhemoglobin concentration. This represents the fourth initial image signal. This represents the second initial image signal.

[0043] It should be noted that the above two calculation formulas are the current industry standard formulas for hemoglobin concentration information. They are merely illustrative examples in this embodiment. If there are other formulas for hemoglobin concentration information in the industry or if the formulas are updated, this embodiment may also use other forms of formulas for hemoglobin concentration information.

[0044] The formula for calculating blood oxygen saturation is:

[0045]

[0046] in, Indicates blood oxygen saturation. This indicates information about oxyhemoglobin concentration. This indicates information about the concentration of deoxyhemoglobin.

[0047] In this embodiment, the second enhanced image signal is obtained by enhancing the brightness of the second initial image signal based on blood oxygen saturation, specifically including steps 251 and 252.

[0048] Step 251, calculate the first gain coefficient based on blood oxygen saturation:

[0049]

[0050] in, Indicates the first gain coefficient. Indicates blood oxygen saturation. Denotes the first constant. This represents the first transformation function.

[0051] Step 252: Multiply the blood oxygenation gain coefficient by the second initial image signal to obtain the second enhanced image signal.

[0052] In this embodiment, a target image is generated based on the second enhanced image signal, the first initial image signal, and the third initial image signal. The target image is used to identify the bleeding location of the target area, specifically including steps 261, 262, and 263.

[0053] Step 261: The second enhanced image signal is used as a guiding signal to perform guided filtering on the first initial image signal to obtain the first enhanced image signal. The first enhanced image signal is used as the B-channel signal of the target image. The band of the first enhanced image signal meets the requirements of the B-channel and can distinguish between coagulated or semi-coagulated blood and blood at the bleeding point.

[0054] Step 262: Generate the G-channel signal and R-channel signal of the target image based on the first enhanced image signal, the second enhanced image signal and the third initial image signal.

[0055] This step specifically includes: generating an intermediate image signal based on the first enhanced image signal, the second enhanced image signal, and the third initial image signal using a spectral inversion method; calculating the hemoglobin concentration information of the target site based on the intermediate image signal and the third initial image signal; calculating the second gain coefficient and the third gain coefficient based on the hemoglobin concentration information; multiplying the second gain coefficient by the intermediate image signal to obtain the G channel signal; and multiplying the third gain coefficient by the third initial image signal to obtain the R channel signal.

[0056] First, based on the first enhanced image signal, the second enhanced image signal, and the third initial image signal, spectral information of a certain wavelength (in this embodiment, it is spectral information at a wavelength of 600nm) can be obtained through spectral inversion. Then, the spectral information is filtered (for example, using a 3×3 digital filter matrix) to obtain an intermediate image signal. In the band of the intermediate image signal, the absorption coefficients of oxyhemoglobin and deoxyhemoglobin are close, so the hemoglobin concentration of the target site can be directly calculated.

[0057] The formula for calculating hemoglobin concentration information is:

[0058]

[0059] in, This indicates hemoglobin concentration information. Indicates the intermediate image signal. This represents the third initial image signal.

[0060] The formula for calculating the second gain coefficient is:

[0061]

[0062] in, This represents the second gain coefficient. Denotes the second constant and the second transformation function;

[0063] The formula for calculating the third gain coefficient is:

[0064]

[0065] in, This represents the third gain coefficient. Represents the second constant. This represents the third transformation function.

[0066] Step 263: Generate the target image based on the B channel signal, G channel signal, and R channel signal.

[0067] In this embodiment, the first transformation function, the second transformation function, and the third transformation function can be the same function or different functions, and can be linear functions, Gaussian functions, etc.

[0068] It should be noted that the first initial image signal, the second initial image signal, the third initial image signal and the fourth initial image signal in this embodiment are acquired by the image sensor on the endoscope. The image sensor can be an RGB-IR image sensor, which can simultaneously acquire information of visible light (such as the 400~720nm band) and near-infrared IR (such as the 800~900nm band).

[0069] This application also provides an application scenario in which the aforementioned endoscopic image processing method based on blood oxygen saturation and multi-center wavelength is used to identify the location of bleeding points in a patient's digestive tract. In this scenario, it is first necessary to enter the patient's digestive tract through an endoscope to obtain a first initial image signal, a second initial image signal, a third initial image signal, and a fourth initial image signal for the patient's digestive tract. That is, the target area involved in the endoscopic image processing method is the digestive tract.

[0070] Based on the same inventive concept, this application also provides an embodiment for implementing the above-mentioned endoscopic image processing method based on blood oxygen saturation and multi-center wavelength. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the endoscopic image processing device based on blood oxygen saturation and multi-center wavelength provided below can be found in the limitations of the endoscopic image processing method based on blood oxygen saturation and multi-center wavelength described above, and will not be repeated here.

[0071] In one exemplary embodiment, an endoscopic image processing apparatus based on blood oxygen saturation and multi-center wavelengths is provided, comprising:

[0072] The image signal acquisition module is used to acquire a first initial image signal, a second initial image signal, a third initial image signal, and a fourth initial image signal; wherein the first initial image signal, the second initial image signal, the third initial image signal, and the fourth initial image signal are image signals obtained by irradiating the target part with light of a first band, a second band, a third band, and a fourth band, respectively, the first band being 395nm-450nm, the second band being 444nm-636nm, the third band being 605nm-635nm, and the fourth band being 812.5nm-837.5nm.

[0073] The oxyhemoglobin calculation module is used to calculate the oxyhemoglobin concentration information of the target site based on the second initial image signal and the third initial image signal.

[0074] The deoxyhemoglobin calculation module is used to calculate the deoxyhemoglobin concentration information of the target site based on the second initial image signal and the fourth initial image signal.

[0075] The blood oxygen saturation calculation module is used to calculate the blood oxygen saturation of the target site based on the oxygenated hemoglobin concentration information and the deoxygenated hemoglobin concentration information.

[0076] The image signal generation module is used to enhance the brightness of the second initial image signal based on blood oxygen saturation to obtain a second enhanced image signal.

[0077] The target image generation module is used to generate a target image based on the second enhanced image signal, the first initial image signal, and the third initial image signal. The target image is used to identify the bleeding location of the target site.

[0078] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0079] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0080] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0081] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0082] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0083] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0084] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0085] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An endoscope image processing method based on blood oxygen saturation and multi-center wavelength, characterized by, The endoscope image processing method comprises: obtaining a first initial image signal, a second initial image signal, a third initial image signal and a fourth initial image signal; wherein the first initial image signal, the second initial image signal, the third initial image signal and the fourth initial image signal are image signals obtained by irradiating a target site with light of a first waveband, a second waveband, a third waveband and a fourth waveband respectively, the first waveband being 395nm-450nm, the second waveband being 444nm-636nm, the third waveband being 605nm-635nm, and the fourth waveband being 812.5nm-837.5nm; calculating oxygenated hemoglobin concentration information of the target site according to the second initial image signal and the third initial image signal; calculating deoxygenated hemoglobin concentration information of the target site according to the second initial image signal and the fourth initial image signal; calculating blood oxygen saturation of the target site according to the oxygenated hemoglobin concentration information and the deoxygenated hemoglobin concentration information; and performing brightness enhancement on the second initial image signal based on the blood oxygen saturation to obtain a second enhanced image signal; performing guided filtering on the first initial image signal based on the second enhanced image signal as a guide signal to obtain a first enhanced image signal, the first enhanced image signal serving as a B channel signal of a target image; generating an intermediate image signal by a spectral inversion method based on the first enhanced image signal, the second enhanced image signal and the third initial image signal; calculating hemoglobin concentration information of the target site according to the intermediate image signal and the third initial image signal; calculating a second gain coefficient and a third gain coefficient according to the hemoglobin concentration information; multiplying the second gain coefficient with the intermediate image signal to obtain a G channel signal; and multiplying the third gain coefficient with the third initial image signal to obtain an R channel signal; generating a target image according to the B channel signal, the G channel signal and the R channel signal, the target image being used to identify a bleeding position of the target site.

2. The method of claim 1, wherein the method is based on blood oxygen saturation and multi-centric wavelength of endoscopic image processing. The calculation formula of the oxygenated hemoglobin concentration information is: wherein represents the oxyhemoglobin concentration information, represents the third initial image signal, represents the second initial image signal.

3. The method of claim 1, wherein the method is based on blood oxygen saturation and multi-centric wavelength of endoscopic image processing. The calculation formula of the deoxygenated hemoglobin concentration information is: wherein represents the deoxyhemoglobin concentration information, represents the fourth initial image signal, represents the second initial image signal.

4. The method of claim 1, wherein the method is based on blood oxygen saturation and multi-centric wavelength of endoscopic image processing. The calculation formula of the blood oxygen saturation is: wherein, represents the blood oxygen saturation, represents the oxyhemoglobin concentration information, represents the deoxyhemoglobin concentration information.

5. The method of claim 1, wherein the method is based on blood oxygen saturation and multi-centric wavelength of endoscopic image processing. performing brightness enhancement on the second initial image signal based on the blood oxygen saturation to obtain a second enhanced image signal, specifically comprising: calculating a first gain coefficient based on the blood oxygen saturation: wherein denotes the first gain coefficient, denotes the blood oxygen saturation, denotes a first constant, denotes a first conversion function; multiplying the blood oxygen gain coefficient with the second initial image signal to obtain the second enhanced image signal.

6. The method of claim 1, wherein, The calculation formula of the hemoglobin concentration information is: wherein, represents the hemoglobin concentration information, represents the intermediate image signal, represents the third initial image signal; The calculation formula of the second gain coefficient is: wherein denotes the second gain coefficient, denotes a second constant, denotes a second conversion function; The calculation formula of the third gain coefficient is: wherein denotes the third gain coefficient, denotes a second constant, denotes a third conversion function.

7. A computer device comprising: a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the endoscope image processing method based on blood oxygen saturation and multi-center wavelength according to any one of claims 1-6.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by a processor, implements the method of processing an endoscopic image based on blood oxygen saturation and multi-center wavelengths according to any one of claims 1-6.

Images