Gastroscopy result-based digestive tract lesion analysis method and system and medium

Abstract

The invention provides a digestive tract lesion analysis method and system based on gastroscopy results and a medium. The method comprises the following steps: acquiring esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters, calculating to obtain an upper digestive tract lesion risk index and a digestive tract comprehensive lesion risk index, and comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold to obtain a digestive tract lesion level, obtaining a corresponding treatment scheme according to the lesion level of the digestive tract; therefore, by combining calculation of the upper digestive tract lesion risk index and the digestive tract comprehensive lesion risk index with threshold comparison, digestive tract lesion analysis is achieved, and a corresponding processing scheme is obtained.

Description

Technical Field

[0001] The present application relates to the field of digestive tract lesion analysis, and specifically, to a digestive tract lesion analysis method, system and medium based on gastroscopy results. Background Art

[0002] Digestive tract diseases are a common type of disease that seriously affects people's health. Gastroscopy, as an important means of digestive tract examination, can directly observe the mucosal lesions of the esophagus, stomach and duodenum, and is one of the important means of diagnosing digestive tract lesions. However, the current analysis of gastroscopy results mainly relies on the doctor's experience to make subjective judgments, and lacks a systematic and objective analysis method. This not only causes low efficiency in the analysis of examination results, but may also lead to missed diagnosis and misdiagnosis of lesions, affecting the health status of patients. Therefore, there is a need for an intelligent digestive tract lesion analysis that can quickly and accurately analyze digestive tract lesions based on the results of gastroscopy.

[0003] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0004] The purpose of this application is to provide a method, system and medium for analyzing gastrointestinal lesions based on the results of gastroscopy, which can realize the technology of analyzing gastrointestinal lesions and obtaining corresponding treatment plans by calculating the upper gastrointestinal lesion risk index and the comprehensive gastrointestinal lesion risk index combined with threshold comparison.

[0005] The present application also provides a method for analyzing digestive tract lesions based on gastroscopy results, comprising the following steps:

[0006] Acquire gastroscopy feature data, and extract esophageal examination feature parameters, stomach examination feature parameters, and duodenum examination feature parameters;

[0007] Obtaining an upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters;

[0008] The duodenal examination characteristic parameters are combined with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index;

[0009] Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold, and obtaining a digestive tract lesion grade according to the threshold comparison result;

[0010] The digestive tract lesion grade is matched with a preset digestive tract lesion grade database, and a corresponding treatment plan is obtained and sent to the smart terminal.

[0011] Optionally, in the digestive tract lesion analysis method based on gastroscopy results described in the present application, the step of obtaining gastroscopy feature data and extracting esophageal examination feature parameters, stomach examination feature parameters and duodenum examination feature parameters specifically includes:

[0012] Extracting esophageal examination characteristic parameters, including esophageal lesion color data, esophageal lesion texture data, and esophageal lesion morphological characteristic data;

[0013] Extract gastric examination characteristic parameters, including gastric mucosal color data, gastric lesion morphological characteristic data, and gastric motility parameters;

[0014] Extract duodenal examination characteristic parameters, including lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data.

[0015] Optionally, in the digestive tract lesion analysis method based on gastroscopy results described in the present application, the obtaining of the upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters specifically includes:

[0016] Calculate the esophageal lesion index according to the esophageal lesion color data, the esophageal lesion texture data and the esophageal lesion morphological feature data;

[0017] Obtaining a gastric lesion index according to the gastric mucosal color data, gastric lesion morphological characteristic data and gastric peristalsis parameter processing;

[0018] The upper gastrointestinal lesion risk index is obtained by processing the esophageal lesion index and the gastric lesion index using a preset upper gastrointestinal lesion risk assessment model.

[0019] Optionally, in the digestive tract lesion analysis method based on gastroscopy results described in the present application, the digestive tract comprehensive lesion risk index is obtained by combining the duodenal examination characteristic parameters with the upper digestive tract lesion risk index, specifically including:

[0020] The lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data are combined with the upper digestive tract lesion risk index through a preset digestive tract comprehensive lesion risk assessment model to obtain a digestive tract comprehensive lesion risk index;

[0021] The calculation formula of the digestive tract comprehensive lesion risk index in the digestive tract comprehensive lesion risk assessment model is:

[0022]

[0023] Among them, X z is the comprehensive risk index of digestive tract lesions, B x , B g , B d , Sx They are lesion morphological characteristic data, lesion smoothness change data, lesion texture characteristic data and upper gastrointestinal lesion risk index, and α1, α2, α3, β, and χ are preset characteristic coefficients.

[0024] Optionally, in the digestive tract lesion analysis method based on gastroscopy results described in the present application, the digestive tract comprehensive lesion risk index is compared with a preset digestive tract comprehensive lesion risk threshold, and the digestive tract lesion grade is obtained according to the threshold comparison result, specifically including:

[0025] Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold to obtain a digestive tract lesion grade;

[0026] Extracting a first threshold and a second threshold according to the digestive tract comprehensive lesion risk threshold, wherein the first threshold is greater than the second threshold;

[0027] comparing the digestive tract comprehensive lesion risk index with the first threshold and the second threshold;

[0028] If the digestive tract comprehensive lesion risk index is greater than the first threshold, the digestive tract lesion level is a severe level;

[0029] If the digestive tract comprehensive lesion risk index is greater than the second threshold and less than or equal to the first threshold, the digestive tract lesion level is moderate;

[0030] If the comprehensive digestive tract lesion risk index is less than or equal to the second threshold, the digestive tract lesion level is a mild level.

[0031] Optionally, in the digestive tract lesion analysis method based on gastroscopy results described in the present application, matching the digestive tract lesion grade with a preset digestive tract lesion grade database, obtaining a corresponding treatment plan and sending it to the smart terminal specifically includes:

[0032] Inputting the digestive tract lesion grade into a preset digestive tract lesion grade database for matching to obtain a corresponding treatment plan;

[0033] If the digestive tract lesion level is mild, the treatment plan is conventional health care treatment;

[0034] If the digestive tract lesion is of moderate grade, the treatment plan is to further strengthen the examination;

[0035] If the gastrointestinal lesion level is severe, the treatment plan is intensive monitoring.

[0036] In a second aspect, the present application provides a digestive tract lesion analysis system based on gastroscopy results, the system comprising: a memory and a processor, the memory storing a program of a digestive tract lesion analysis method based on gastroscopy results, the program of the digestive tract lesion analysis method based on gastroscopy results when executed by the processor implements the following steps:

[0037] Acquire gastroscopy feature data, and extract esophageal examination feature parameters, stomach examination feature parameters, and duodenum examination feature parameters;

[0038] Obtaining an upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters;

[0039] The duodenal examination characteristic parameters are combined with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index;

[0040] Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold, and obtaining a digestive tract lesion grade according to the threshold comparison result;

[0041] The digestive tract lesion grade is matched with a preset digestive tract lesion grade database, and a corresponding treatment plan is obtained and sent to the smart terminal.

[0042] Optionally, in the digestive tract lesion analysis system based on gastroscopy results described in the present application, the obtaining of gastroscopy feature data and the extraction of esophageal examination feature parameters, stomach examination feature parameters and duodenum examination feature parameters specifically include:

[0043] Extracting esophageal examination characteristic parameters, including esophageal lesion color data, esophageal lesion texture data, and esophageal lesion morphological characteristic data;

[0044] Extract gastric examination characteristic parameters, including gastric mucosal color data, gastric lesion morphological characteristic data, and gastric motility parameters;

[0045] Extract duodenal examination characteristic parameters, including lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data.

[0046] Optionally, in the digestive tract lesion analysis system based on gastroscopy results described in the present application, the obtaining of the upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters comprises:

[0047] Calculate the esophageal lesion index according to the esophageal lesion color data, the esophageal lesion texture data and the esophageal lesion morphological feature data;

[0048] Obtaining a gastric lesion index according to the gastric mucosal color data, gastric lesion morphological characteristic data and gastric peristalsis parameter processing;

[0049] The upper gastrointestinal lesion risk index is obtained by processing the esophageal lesion index and the gastric lesion index using a preset upper gastrointestinal lesion risk assessment model.

[0050] In a third aspect, the present application also provides a readable storage medium, which stores a program for a method for analyzing gastrointestinal lesions based on the results of gastroscopy. When the program for analyzing gastrointestinal lesions based on the results of gastroscopy is executed by a processor, the steps of the method for analyzing gastrointestinal lesions based on the results of gastroscopy as described in any one of the above items are implemented.

[0051] As can be seen from the above, the present application provides a method, system and medium for analyzing digestive tract lesions based on gastroscopy results. The method obtains the esophageal examination characteristic parameters, the stomach examination characteristic parameters and the duodenal examination characteristic parameters and calculates the upper digestive tract lesion risk index and the digestive tract comprehensive lesion risk index, compares the digestive tract comprehensive lesion risk index with the preset digestive tract comprehensive lesion risk threshold to obtain the digestive tract lesion grade, and obtains the corresponding treatment plan according to the digestive tract lesion grade; thus, the technology of digestive tract lesion analysis and obtaining the corresponding treatment plan is realized by calculating the upper digestive tract lesion risk index and the digestive tract comprehensive lesion risk index in combination with the threshold comparison.

[0052] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures particularly pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A flowchart of a method for analyzing digestive tract lesions based on gastroscopy results provided in an embodiment of the present application;

[0055] Figure 2 A flowchart of obtaining esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters of a method for analyzing digestive tract lesions based on gastroscopy results provided in an embodiment of the present application;

[0056] Figure 3 A flow chart of obtaining an upper gastrointestinal lesion risk index for a gastrointestinal lesion analysis method based on gastroscopy results provided in an embodiment of the present application;

[0057] Figure 4 A flow chart of obtaining the grade of digestive tract lesions in a method for analyzing digestive tract lesions based on gastroscopy results provided in an embodiment of the present application. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0059] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0060] Please refer to Figure 1 , Figure 1 The present invention is a flowchart of a method for analyzing digestive tract lesions based on gastroscopy results in some embodiments of the present invention. The method for analyzing digestive tract lesions based on gastroscopy results is used in a terminal device, such as a computer, a mobile phone, etc. The method for analyzing digestive tract lesions based on gastroscopy results comprises the following steps:

[0061] S11, obtaining gastroscopy feature data, and extracting esophageal examination feature parameters, stomach examination feature parameters, and duodenum examination feature parameters;

[0062] S12, obtaining an upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters;

[0063] S13, combining the duodenal examination characteristic parameters with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index;

[0064] S14, comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold, and obtaining a digestive tract lesion grade according to the threshold comparison result;

[0065] S15. Match the digestive tract lesion grade with a preset digestive tract lesion grade database, obtain a corresponding treatment plan and send it to the smart terminal.

[0066] It should be noted that in gastroscopy, three parts are mainly examined, namely the esophagus, stomach and duodenum. The examination data of the esophagus, stomach and duodenum represent the condition of the digestive tract. Therefore, the esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters in the gastroscopy results are obtained. The obtained parameters reflect the inspection status of each part. The upper gastrointestinal tract lesion risk index is calculated based on the esophageal examination characteristic parameters and stomach examination characteristic parameters. The upper gastrointestinal tract lesion risk index is then processed with the duodenal examination characteristic parameters to obtain the digestive tract comprehensive lesion risk index. The digestive tract comprehensive lesion index is a measure of the digestive tract lesion situation. It is compared with the preset digestive tract comprehensive lesion risk threshold to obtain the digestive tract lesion grade. Different grades represent different degrees of lesions. The corresponding treatment plan is obtained according to the digestive tract lesion grade matching and sent to the smart terminal for display.

[0067] Please refer to Figure 2 , Figure 2 The present invention provides a flowchart of obtaining esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters of a method for analyzing digestive tract lesions based on gastroscopy results provided in an embodiment of the present application. According to an embodiment of the present invention, obtaining gastroscopy characteristic data and extracting esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters specifically include:

[0068] S21, extracting esophageal examination characteristic parameters, including esophageal lesion color data, esophageal lesion texture data, and esophageal lesion morphological characteristic data;

[0069] S22, extracting stomach examination characteristic parameters, including gastric mucosal color data, gastric lesion morphological characteristic data, and gastric motility parameters;

[0070] S23. Extracting duodenal examination characteristic parameters, including lesion morphological characteristic data, lesion smoothness change data, and lesion texture characteristic data.

[0071] It should be noted that the results of gastroscopy mainly include three parts of data, esophageal examination characteristic parameters, gastric examination characteristic parameters and duodenal examination characteristic parameters. During the esophageal inspection process, the color, texture and morphological characteristic data of the esophageal mucosa are mainly detected and observed. Redness of the digestive tract tissue indicates inflammation, congestion, etc.; whitening is related to mucosal atrophy, intestinal metaplasia, etc.; esophageal lesion color data refers to the color data after comprehensive consideration of the whitening location and redness location and size; esophageal lesion texture data refers to the comprehensive texture data obtained after comprehensive consideration of the normal esophageal texture and lesion texture; esophageal lesion morphological characteristic data refers to the comprehensive consideration of esophageal erosion, tumors, and ulcers. The data reflecting the morphology of the lesion is obtained by considering the size, shape and surface characteristics of the gastric mucosa; the gastric mucosal color data refers to the color data after comprehensively considering the white and red parts of the gastric mucosa and the size; the gastric lesion morphological characteristic data refers to the data reflecting the lesion morphology after comprehensively considering the size, shape and surface characteristics of gastric erosions, tumors and ulcers; the gastric motility parameter refers to the data obtained by comparing the real-time monitoring of gastric motility with the normal standard situation; the lesion smoothness change data refers to the data reflecting the smoothness obtained by comparing the smoothness of the duodenum examination with the normal smoothness; the lesion texture characteristic data refers to the data reflecting the softness and hardness of the lesion part.

[0072] Please refer to Figure 3 , Figure 3 The present invention provides a flowchart of obtaining an upper gastrointestinal lesion risk index according to a method for analyzing gastrointestinal lesions based on gastroscopy results. According to an embodiment of the present invention, obtaining an upper gastrointestinal lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters specifically includes:

[0073] S31, calculating and obtaining an esophageal lesion index according to the esophageal lesion color data, the esophageal lesion texture data and the esophageal lesion morphological feature data;

[0074] S32, obtaining a gastric lesion index according to the gastric mucosal color data, gastric lesion morphological characteristic data and gastric peristalsis parameter processing;

[0075] S33. Obtain an upper gastrointestinal lesion risk index based on the esophageal lesion index and the gastric lesion index through a preset upper gastrointestinal lesion risk assessment model.

[0076] It should be noted that to analyze the digestive tract lesions, it is necessary to analyze the conditions of each part. In gastroscopy, the upper digestive tract includes the esophagus and stomach. It is necessary to calculate the lesion index of the esophagus and stomach separately. The calculation formula of the esophageal lesion index is:

[0077]

[0078] Among them, S bS is the esophageal lesion index, ys , S wl , S xt They are esophageal lesion color data, esophageal lesion texture data and esophageal lesion morphological feature data, respectively; δ1, δ2 and δ3 are preset feature coefficients (the feature coefficients are obtained by querying the preset digestive tract lesion analysis platform based on gastroscopy results);

[0079] The calculation formula of gastric lesion index is:

[0080]

[0081] Among them, W b is the gastric lesion index, W sz , W xt , W rd They are gastric mucosal color data, gastric lesion morphological characteristic data and gastric motility parameters, respectively; γ1, γ2 and γ3 are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset digestive tract lesion analysis platform based on gastroscopy results);

[0082] The upper gastrointestinal tract lesion risk index calculation formula is:

[0083]

[0084] Among them, S x is the risk index of upper gastrointestinal tract lesions, S b is the esophageal lesion index, W b is the gastric lesion index, and η1, η2, and η3 are preset characteristic coefficients (the characteristic coefficients are obtained by querying the gastrointestinal lesion analysis platform based on the preset gastroscopy results).

[0085] According to an embodiment of the present invention, the combining of the duodenal examination characteristic parameters with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index specifically includes:

[0086] The lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data are combined with the upper digestive tract lesion risk index through a preset digestive tract comprehensive lesion risk assessment model to obtain a digestive tract comprehensive lesion risk index;

[0087] The calculation formula of the digestive tract comprehensive lesion risk index in the digestive tract comprehensive lesion risk assessment model is:

[0088]

[0089] Among them, X z is the comprehensive risk index of digestive tract lesions, B x , B g , B d , Sx They are lesion morphological characteristic data, lesion smoothness change data, lesion texture characteristic data and upper gastrointestinal lesion risk index, and α1, α2, α3, β, and χ are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset gastrointestinal lesion analysis platform based on gastroscopy results).

[0090] It should be noted that after obtaining the upper gastrointestinal lesion risk index, it is necessary to consider the lesion risk of the duodenum to obtain the comprehensive gastrointestinal lesion risk index, so that a comprehensive analysis of gastrointestinal lesions can be conducted. The comprehensive gastrointestinal lesion risk index refers to data that can comprehensively reflect the risk of gastrointestinal lesions to a certain extent. The larger the comprehensive gastrointestinal lesion risk index, the higher the risk.

[0091] Please refer to Figure 4 , Figure 4 The present invention provides a flowchart of a method for analyzing digestive tract lesions based on gastroscopy results to obtain a digestive tract lesion grade. According to an embodiment of the present invention, the digestive tract comprehensive lesion risk index is compared with a preset digestive tract comprehensive lesion risk threshold, and the digestive tract lesion grade is obtained according to the threshold comparison result, specifically including:

[0092] S41, comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold to obtain a digestive tract lesion grade;

[0093] S42, extracting a first threshold and a second threshold according to the digestive tract comprehensive lesion risk threshold, and the first threshold is greater than the second threshold;

[0094] S43, comparing the digestive tract comprehensive lesion risk index with the first threshold and the second threshold;

[0095] S44. If the digestive tract comprehensive lesion risk index is greater than the first threshold, the digestive tract lesion level is a severe level;

[0096] S45. If the digestive tract comprehensive lesion risk index is greater than the second threshold and less than or equal to the first threshold, the digestive tract lesion grade is moderate;

[0097] S46. If the comprehensive digestive tract lesion risk index is less than or equal to the second threshold, the digestive tract lesion level is a mild level.

[0098] It should be noted that after calculating the comprehensive gastrointestinal lesion risk index, in order to more intuitively understand the lesion level, it is necessary to obtain the gastrointestinal lesion level through threshold comparison. In this embodiment, the comprehensive gastrointestinal lesion risk threshold is set to: (0, 0.5], which is a mild level; (0.5, 0.7], which is a moderate level; (0.7, 1], which is a severe level; when the comprehensive gastrointestinal lesion risk index is 0.9, the gastrointestinal lesion level is a severe level.

[0099] According to an embodiment of the present invention, matching the digestive tract lesion grade with a preset digestive tract lesion grade database, obtaining a corresponding treatment plan and sending it to the smart terminal specifically includes:

[0100] Inputting the digestive tract lesion grade into a preset digestive tract lesion grade database for matching to obtain a corresponding treatment plan;

[0101] If the digestive tract lesion level is mild, the treatment plan is conventional health care treatment;

[0102] If the digestive tract lesion is of moderate grade, the treatment plan is to further strengthen the examination;

[0103] If the gastrointestinal lesion level is severe, the treatment plan is intensive monitoring.

[0104] It should be noted that the preset gastrointestinal lesion level database contains the gastrointestinal lesion level, treatment plan and the mapping relationship between the two. After obtaining the gastrointestinal lesion level, the treatment plan is automatically matched. Conventional health care treatment refers to the use of conventional means for gastrointestinal rehabilitation; further strengthened inspection means that in order to more determine the condition of gastrointestinal lesions, more precise inspections are needed, such as biopsy; key monitoring means that the gastrointestinal lesions are already very serious and require key monitoring.

[0105] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0106] Obtain gastroscopy equipment status information and extract gastroscopy equipment status data, including cumulative operating time data, time from last calibration data, and equipment operating electrical deviation data;

[0107] Input the accumulated running time data, the time data from the last calibration, and the equipment running electrical deviation data into a preset gastroscopy equipment deviation evaluation model for processing to obtain a gastroscopy deviation index;

[0108] Comparing the gastroscopy deviation index with a preset gastroscopy deviation threshold to obtain a working state of the gastroscopy device, including a normal state or an abnormal state;

[0109] If the gastroscopy deviation index is less than or equal to the preset gastroscopy deviation threshold, the working state of the gastroscopy device is normal, and the detection data is valid;

[0110] If the gastroscopy deviation index is greater than the preset gastroscopy deviation threshold, the working state of the gastroscopy device is abnormal, and the detection data needs to be confirmed;

[0111] The calculation formula of the gastroscopy deviation index in the gastroscopy equipment deviation evaluation model is:

[0112]

[0113] Among them, J x is the gastroscopy deviation index, L j , J s , P c They are respectively the accumulated operating time data, the time data from the last calibration and the equipment operating electrical deviation data. ε1, ε2, ε3 and ε4 are the preset characteristic coefficients.

[0114] It should be noted that the working status and working time of the gastroscopy equipment affect the accuracy of the inspection data. After the gastroscopy equipment has been working for a period of time, it needs maintenance and calibration. In addition, the electrical data of the equipment operation will also cause deviations in the inspection data. If the equipment is used for too long, it will also affect the deviation of the inspection data. Therefore, in order to better ensure the accuracy of the inspection data, it is necessary to comprehensively consider the cumulative operating time data, the time data from the last calibration and the equipment operating electrical deviation data; the cumulative operating time data refers to the total cumulative working time data since the equipment was purchased and used, and the time data from the last calibration refers to the time from the last maintenance to this inspection The time taken for the inspection to be completed; the electrical deviation data of the equipment operation refers to the difference data between the real-time electrical parameters and the standard electrical parameters when the inspection equipment is running; the gastroscopy deviation index refers to the deviation ratio between the inspection result under the actual state and the normal inspection result compared with the normal inspection result obtained under the standard state; the working state of the gastroscopy equipment can be obtained after the threshold comparison; in this embodiment, the gastroscopy deviation threshold is set to: (0, 0.35], the working state of the gastroscopy equipment is normal; (0.35, 1], the working state of the gastroscopy equipment is abnormal; when the gastroscopy deviation index is 0.3, the working state of the gastroscopy equipment is normal.

[0115] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0116] Obtain the examiner's rehabilitation program data and effective historical gastroscopy characteristics data, and calculate the inspection interval time data and historical digestive tract comprehensive lesion risk index;

[0117] Dividing the digestive tract comprehensive lesion risk index by the historical digestive tract comprehensive lesion risk index to obtain a digestive tract comprehensive lesion recovery factor;

[0118] Obtain a digestive tract rehabilitation program database, including rehabilitation program data and corresponding rehabilitation duration averages and digestive tract comprehensive lesion rehabilitation standard factor data;

[0119] According to the use of the rehabilitation program data and the digestive tract rehabilitation program database, the corresponding rehabilitation time average and digestive tract comprehensive disease rehabilitation standard factor data are obtained;

[0120] The rehabilitation program effectiveness index is calculated based on the test interval duration data, the mean rehabilitation duration, the digestive tract comprehensive lesion rehabilitation factor, and the digestive tract comprehensive lesion rehabilitation standard factor data;

[0121] The calculation formula of the effectiveness index of the rehabilitation program is:

[0122]

[0123] Among them, K y is the rehabilitation program effectiveness index, J j To test the interval duration data, K j is the mean recovery time, K yz K is the digestive tract comprehensive disease recovery factor, by is the digestive tract comprehensive lesion rehabilitation standard factor data, γ1 and γ2 are the preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset digestive tract lesion analysis platform based on gastroscopy results);

[0124] Comparing the rehabilitation program effectiveness index with a preset rehabilitation program effectiveness index threshold to obtain the rehabilitation program effect status;

[0125] If the rehabilitation program effectiveness index is greater than or equal to the rehabilitation program effectiveness index threshold, the rehabilitation program effect status is effective;

[0126] If the rehabilitation program effectiveness index is less than the rehabilitation program effectiveness index threshold, the rehabilitation program effect status is in a pending adjustment status.

[0127] Among them, there are many examiners who undergo reexamination. The reexaminers undergo a certain period of rehabilitation and then further examine the recovery status. Not all patients may be improved during the reexamination. Therefore, it is necessary to judge the effectiveness of the rehabilitation program for the patient and determine whether the program is more effective for the patient himself. The effective judgment standard is whether the patient's recovery status is higher than the average recovery status under the program. The effective historical gastroscopy feature data refers to the gastroscopy feature data of the most recent examination that meets the reexamination cycle from the time of the current examination. The inspection interval time data refers to the time data from the current examination to the last effective examination time. The digestive tract comprehensive lesion rehabilitation factor refers to the degree of recovery relative to the historical examination situation. The rehabilitation time mean data refers to the mean time used by patients who are effective in adopting the rehabilitation program to recover to the digestive tract comprehensive lesion rehabilitation standard factor data; in this embodiment, the rehabilitation program effectiveness index threshold is set to: [0,0.7), the rehabilitation program effect state is to be adjusted; [0.7,1], the rehabilitation program effect state is effective; when the rehabilitation program effectiveness index is 0.9, the rehabilitation program effect state is effective.

[0128] The present invention also discloses a digestive tract lesion analysis system based on gastroscopy results, comprising a memory and a processor, wherein the memory stores a digestive tract lesion analysis method program based on gastroscopy results, and when the digestive tract lesion analysis method program based on gastroscopy results is executed by the processor, the following steps are implemented:

[0129] Acquire gastroscopy feature data, and extract esophageal examination feature parameters, stomach examination feature parameters, and duodenum examination feature parameters;

[0130] Obtaining an upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters;

[0131] The duodenal examination characteristic parameters are combined with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index;

[0132] Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold, and obtaining a digestive tract lesion grade according to the threshold comparison result;

[0133] The digestive tract lesion grade is matched with a preset digestive tract lesion grade database, and a corresponding treatment plan is obtained and sent to the smart terminal.

[0134] It should be noted that in gastroscopy, three parts are mainly examined, namely the esophagus, stomach and duodenum. The examination data of the esophagus, stomach and duodenum represent the condition of the digestive tract. Therefore, the esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters in the gastroscopy results are obtained. The obtained parameters reflect the inspection status of each part. The upper gastrointestinal tract lesion risk index is calculated based on the esophageal examination characteristic parameters and stomach examination characteristic parameters. The upper gastrointestinal tract lesion risk index is then processed with the duodenal examination characteristic parameters to obtain the digestive tract comprehensive lesion risk index. The digestive tract comprehensive lesion index is a measure of the digestive tract lesion situation. It is compared with the preset digestive tract comprehensive lesion risk threshold to obtain the digestive tract lesion grade. Different grades represent different degrees of lesions. The corresponding treatment plan is obtained according to the digestive tract lesion grade matching and sent to the smart terminal for display.

[0135] According to an embodiment of the present invention, the step of acquiring gastroscopy feature data and extracting esophageal examination feature parameters, stomach examination feature parameters and duodenum examination feature parameters specifically includes:

[0136] Extracting esophageal examination characteristic parameters, including esophageal lesion color data, esophageal lesion texture data, and esophageal lesion morphological characteristic data;

[0137] Extract gastric examination characteristic parameters, including gastric mucosal color data, gastric lesion morphological characteristic data, and gastric motility parameters;

[0138] Extract duodenal examination characteristic parameters, including lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data.

[0139] It should be noted that the results of gastroscopy mainly include three parts of data, esophageal examination characteristic parameters, gastric examination characteristic parameters and duodenal examination characteristic parameters. During the esophageal inspection process, the color, texture and morphological characteristic data of the esophageal mucosa are mainly detected and observed. Redness of the digestive tract tissue indicates inflammation, congestion, etc.; whitening is related to mucosal atrophy, intestinal metaplasia, etc.; esophageal lesion color data refers to the color data after comprehensive consideration of the whitening location and redness location and size; esophageal lesion texture data refers to the comprehensive texture data obtained after comprehensive consideration of the normal esophageal texture and lesion texture; esophageal lesion morphological characteristic data refers to the comprehensive consideration of esophageal erosion, tumors, and ulcers. The data reflecting the morphology of the lesion is obtained by considering the size, shape and surface characteristics of the gastric mucosa; the gastric mucosal color data refers to the color data after comprehensively considering the white and red parts of the gastric mucosa and the size; the gastric lesion morphological characteristic data refers to the data reflecting the lesion morphology after comprehensively considering the size, shape and surface characteristics of gastric erosions, tumors and ulcers; the gastric motility parameter refers to the data obtained by comparing the real-time monitoring of gastric motility with the normal standard situation; the lesion smoothness change data refers to the data reflecting the smoothness obtained by comparing the smoothness of the duodenum examination with the normal smoothness; the lesion texture characteristic data refers to the data reflecting the softness and hardness of the lesion part.

[0140] According to an embodiment of the present invention, obtaining the upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters specifically includes:

[0141] Calculate the esophageal lesion index according to the esophageal lesion color data, the esophageal lesion texture data and the esophageal lesion morphological feature data;

[0142] Obtaining a gastric lesion index according to the gastric mucosal color data, gastric lesion morphological characteristic data and gastric peristalsis parameter processing;

[0143] The upper gastrointestinal lesion risk index is obtained by processing the esophageal lesion index and the gastric lesion index using a preset upper gastrointestinal lesion risk assessment model.

[0144] It should be noted that to analyze the digestive tract lesions, it is necessary to analyze the conditions of each part. In gastroscopy, the upper digestive tract includes the esophagus and stomach. It is necessary to calculate the lesion index of the esophagus and stomach separately. The calculation formula of the esophageal lesion index is:

[0145]

[0146] Among them, S b S is the esophageal lesion index, ys , S wl , S xtThey are esophageal lesion color data, esophageal lesion texture data and esophageal lesion morphological feature data, respectively; δ1, δ2 and δ3 are preset feature coefficients (the feature coefficients are obtained by querying the preset digestive tract lesion analysis platform based on gastroscopy results);

[0147] The calculation formula of gastric lesion index is:

[0148]

[0149] Among them, W b is the gastric lesion index, W sz , W xt , W rd They are gastric mucosal color data, gastric lesion morphological characteristic data and gastric motility parameters, respectively; γ1, γ2 and γ3 are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset digestive tract lesion analysis platform based on gastroscopy results);

[0150] The upper gastrointestinal tract lesion risk index calculation formula is:

[0151]

[0152] Among them, S x is the risk index of upper gastrointestinal tract lesions, S b is the esophageal lesion index, W b is the gastric lesion index, and η1, η2, and η3 are preset characteristic coefficients (the characteristic coefficients are obtained by querying the gastrointestinal lesion analysis platform based on the preset gastroscopy results).

[0153] According to an embodiment of the present invention, the combining of the duodenal examination characteristic parameters with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index specifically includes:

[0154] The lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data are combined with the upper digestive tract lesion risk index through a preset digestive tract comprehensive lesion risk assessment model to obtain a digestive tract comprehensive lesion risk index;

[0155] The calculation formula of the digestive tract comprehensive lesion risk index in the digestive tract comprehensive lesion risk assessment model is:

[0156]

[0157] Among them, X z is the comprehensive risk index of digestive tract lesions, B x , B g , B d , S xThey are lesion morphological characteristic data, lesion smoothness change data, lesion texture characteristic data and upper gastrointestinal lesion risk index, and α1, α2, α3, β, and χ are preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset gastrointestinal lesion analysis platform based on gastroscopy results).

[0158] It should be noted that after obtaining the upper gastrointestinal lesion risk index, it is necessary to consider the lesion risk of the duodenum to obtain the comprehensive gastrointestinal lesion risk index, so that a comprehensive analysis of gastrointestinal lesions can be conducted. The comprehensive gastrointestinal lesion risk index refers to data that can comprehensively reflect the risk of gastrointestinal lesions to a certain extent. The larger the comprehensive gastrointestinal lesion risk index, the higher the risk.

[0159] According to an embodiment of the present invention, comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold, and obtaining the digestive tract lesion grade according to the threshold comparison result, specifically includes:

[0160] Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold to obtain a digestive tract lesion grade;

[0161] Extracting a first threshold and a second threshold according to the digestive tract comprehensive lesion risk threshold, wherein the first threshold is greater than the second threshold;

[0162] comparing the digestive tract comprehensive lesion risk index with the first threshold and the second threshold;

[0163] If the digestive tract comprehensive lesion risk index is greater than the first threshold, the digestive tract lesion level is a severe level;

[0164] If the digestive tract comprehensive lesion risk index is greater than the second threshold and less than or equal to the first threshold, the digestive tract lesion level is moderate;

[0165] If the comprehensive digestive tract lesion risk index is less than or equal to the second threshold, the digestive tract lesion level is a mild level.

[0166] It should be noted that after calculating the comprehensive gastrointestinal lesion risk index, in order to more intuitively understand the lesion level, it is necessary to obtain the gastrointestinal lesion level through threshold comparison. In this embodiment, the comprehensive gastrointestinal lesion risk threshold is set to: (0, 0.5], which is a mild level; (0.5, 0.7], which is a moderate level; (0.7, 1], which is a severe level; when the comprehensive gastrointestinal lesion risk index is 0.9, the gastrointestinal lesion level is a severe level.

[0167] According to an embodiment of the present invention, matching the digestive tract lesion grade with a preset digestive tract lesion grade database, obtaining a corresponding treatment plan and sending it to the smart terminal specifically includes:

[0168] Inputting the digestive tract lesion grade into a preset digestive tract lesion grade database for matching to obtain a corresponding treatment plan;

[0169] If the digestive tract lesion level is mild, the treatment plan is conventional health care treatment;

[0170] If the digestive tract lesion is of moderate grade, the treatment plan is to further strengthen the examination;

[0171] If the gastrointestinal lesion level is severe, the treatment plan is intensive monitoring.

[0172] It should be noted that the preset gastrointestinal lesion level database contains the gastrointestinal lesion level, treatment plan and the mapping relationship between the two. After obtaining the gastrointestinal lesion level, the treatment plan is automatically matched. Conventional health care treatment refers to the use of conventional means for gastrointestinal rehabilitation; further strengthened inspection means that in order to more determine the condition of gastrointestinal lesions, more precise inspections are needed, such as biopsy; key monitoring means that the gastrointestinal lesions are already very serious and require key monitoring.

[0173] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0174] Obtain gastroscopy equipment status information and extract gastroscopy equipment status data, including cumulative operating time data, time from last calibration data, and equipment operating electrical deviation data;

[0175] Input the accumulated running time data, the time data from the last calibration, and the equipment running electrical deviation data into a preset gastroscopy equipment deviation evaluation model for processing to obtain a gastroscopy deviation index;

[0176] Comparing the gastroscopy deviation index with a preset gastroscopy deviation threshold to obtain a working state of the gastroscopy device, including a normal state or an abnormal state;

[0177] If the gastroscopy deviation index is less than or equal to the preset gastroscopy deviation threshold, the working state of the gastroscopy device is normal, and the detection data is valid;

[0178] If the gastroscopy deviation index is greater than the preset gastroscopy deviation threshold, the working state of the gastroscopy device is abnormal, and the detection data needs to be confirmed;

[0179] The calculation formula of the gastroscopy deviation index in the gastroscopy equipment deviation evaluation model is:

[0180]

[0181] Among them, Jx is the gastroscopy deviation index, L j , J s , P c They are respectively the accumulated operating time data, the time data from the last calibration and the equipment operating electrical deviation data. ε1, ε2, ε3 and ε4 are the preset characteristic coefficients.

[0182] It should be noted that the working status and working time of the gastroscopy equipment affect the accuracy of the inspection data. After the gastroscopy equipment has been working for a period of time, it needs maintenance and calibration. In addition, the electrical data of the equipment operation will also cause deviations in the inspection data. If the equipment is used for too long, it will also affect the deviation of the inspection data. Therefore, in order to better ensure the accuracy of the inspection data, it is necessary to comprehensively consider the cumulative operating time data, the time data from the last calibration and the equipment operating electrical deviation data; the cumulative operating time data refers to the total cumulative working time data since the equipment was purchased and used, and the time data from the last calibration refers to the time from the last maintenance to this inspection The time taken for the inspection to be completed; the electrical deviation data of the equipment operation refers to the difference data between the real-time electrical parameters and the standard electrical parameters when the inspection equipment is running; the gastroscopy deviation index refers to the deviation ratio between the inspection result under the actual state and the normal inspection result compared with the normal inspection result obtained under the standard state; the working state of the gastroscopy equipment can be obtained after the threshold comparison; in this embodiment, the gastroscopy deviation threshold is set to: (0, 0.35], the working state of the gastroscopy equipment is normal; (0.35, 1], the working state of the gastroscopy equipment is abnormal; when the gastroscopy deviation index is 0.3, the working state of the gastroscopy equipment is normal.

[0183] It is worth mentioning that according to an embodiment of the present invention, it also includes:

[0184] Obtain the examiner's rehabilitation program data and effective historical gastroscopy characteristics data, and calculate the inspection interval time data and historical digestive tract comprehensive lesion risk index;

[0185] Dividing the digestive tract comprehensive lesion risk index by the historical digestive tract comprehensive lesion risk index to obtain a digestive tract comprehensive lesion recovery factor;

[0186] Obtain a digestive tract rehabilitation program database, including rehabilitation program data and corresponding rehabilitation duration averages and digestive tract comprehensive lesion rehabilitation standard factor data;

[0187] According to the use of the rehabilitation program data and the digestive tract rehabilitation program database, the corresponding rehabilitation time average and digestive tract comprehensive disease rehabilitation standard factor data are obtained;

[0188] The rehabilitation program effectiveness index is calculated based on the test interval duration data, the mean rehabilitation duration, the digestive tract comprehensive lesion rehabilitation factor, and the digestive tract comprehensive lesion rehabilitation standard factor data;

[0189] The calculation formula of the effectiveness index of the rehabilitation program is:

[0190]

[0191] Among them, K y is the rehabilitation program effectiveness index, J j To test the interval duration data, K j is the mean recovery time, K yz K is the digestive tract comprehensive disease recovery factor, by is the digestive tract comprehensive lesion rehabilitation standard factor data, γ1 and γ2 are the preset characteristic coefficients (the characteristic coefficients are obtained by querying the preset digestive tract lesion analysis platform based on gastroscopy results);

[0192] Comparing the rehabilitation program effectiveness index with a preset rehabilitation program effectiveness index threshold to obtain the rehabilitation program effect status;

[0193] If the rehabilitation program effectiveness index is greater than or equal to the rehabilitation program effectiveness index threshold, the rehabilitation program effect status is effective;

[0194] If the rehabilitation program effectiveness index is less than the rehabilitation program effectiveness index threshold, the rehabilitation program effect status is in a pending adjustment status.

[0195] Among them, there are many examiners who undergo reexamination. The reexaminers undergo a certain period of rehabilitation and then further examine the recovery status. Not all patients may be improved during the reexamination. Therefore, it is necessary to judge the effectiveness of the rehabilitation program for the patient and determine whether the program is more effective for the patient himself. The effective judgment standard is whether the patient's recovery status is higher than the average recovery status under the program. The effective historical gastroscopy feature data refers to the gastroscopy feature data of the most recent examination that meets the reexamination cycle from the time of the current examination. The inspection interval time data refers to the time data from the current examination to the last effective examination time. The digestive tract comprehensive lesion rehabilitation factor refers to the degree of recovery relative to the historical examination situation. The rehabilitation time mean data refers to the mean time used by patients who are effective in adopting the rehabilitation program to recover to the digestive tract comprehensive lesion rehabilitation standard factor data; in this embodiment, the rehabilitation program effectiveness index threshold is set to: [0,0.7), the rehabilitation program effect state is to be adjusted; [0.7,1], the rehabilitation program effect state is effective; when the rehabilitation program effectiveness index is 0.9, the rehabilitation program effect state is effective.

[0196] A third aspect of the present invention provides a readable storage medium, which includes a program for a method for analyzing gastrointestinal lesions based on gastroscopy results. When the program for analyzing gastrointestinal lesions based on gastroscopy results is executed by a processor, the steps of the method for analyzing gastrointestinal lesions based on gastroscopy results as described in any one of the above items are implemented.

[0197] The present invention discloses a method, system and medium for analyzing gastrointestinal lesions based on gastroscopy results, which obtains esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenal examination characteristic parameters and calculates an upper gastrointestinal lesion risk index and a comprehensive gastrointestinal lesion risk index, compares the comprehensive gastrointestinal lesion risk index with a preset comprehensive gastrointestinal lesion risk threshold to obtain a gastrointestinal lesion grade, and obtains a corresponding treatment plan according to the gastrointestinal lesion grade; thereby, the technology of analyzing gastrointestinal lesions and obtaining corresponding treatment plans is realized by calculating the upper gastrointestinal lesion risk index and the comprehensive gastrointestinal lesion risk index in combination with threshold comparison.

[0198] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0199] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0200] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0201] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0202] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for analyzing digestive tract lesions based on gastroscopy results, characterized in that: include: Acquire gastroscopy feature data, and extract esophageal examination feature parameters, stomach examination feature parameters, and duodenum examination feature parameters; Obtaining an upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters; The duodenal examination characteristic parameters are combined with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index; Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold, and obtaining a digestive tract lesion grade according to the threshold comparison result; The digestive tract lesion grade is matched with a preset digestive tract lesion grade database, and a corresponding treatment plan is obtained and sent to the smart terminal.

2. The method for analyzing digestive tract lesions based on gastroscopy results according to claim 1, characterized in that: The obtaining of gastroscopy characteristic data and the extraction of esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters specifically include: Extracting esophageal examination characteristic parameters, including esophageal lesion color data, esophageal lesion texture data, and esophageal lesion morphological characteristic data; Extract gastric examination characteristic parameters, including gastric mucosal color data, gastric lesion morphological characteristic data, and gastric motility parameters; Extract duodenal examination characteristic parameters, including lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data.

3. The method for analyzing digestive tract lesions based on gastroscopy results according to claim 2, characterized in that: The step of obtaining the upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters specifically includes: Calculate the esophageal lesion index according to the esophageal lesion color data, the esophageal lesion texture data and the esophageal lesion morphological feature data; Obtaining a gastric lesion index according to the gastric mucosal color data, gastric lesion morphological characteristic data and gastric peristalsis parameter processing; The upper gastrointestinal lesion risk index is obtained by processing the esophageal lesion index and the gastric lesion index using a preset upper gastrointestinal lesion risk assessment model.

4. The method for analyzing digestive tract lesions based on gastroscopy results according to claim 3, characterized in that: The step of combining the duodenal examination characteristic parameters with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index specifically includes: The lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data are combined with the upper digestive tract lesion risk index through a preset digestive tract comprehensive lesion risk assessment model to obtain a digestive tract comprehensive lesion risk index; The calculation formula of the digestive tract comprehensive lesion risk index in the digestive tract comprehensive lesion risk assessment model is: Among them, X z is the comprehensive risk index of digestive tract lesions, B x , B g , B d , S x They are lesion morphological characteristic data, lesion smoothness change data, lesion texture characteristic data and upper gastrointestinal lesion risk index, and α1, α2, α3, β, and χ are preset characteristic coefficients.

5. The method for analyzing digestive tract lesions based on gastroscopy results according to claim 4, characterized in that: The digestive tract comprehensive lesion risk index is compared with a preset digestive tract comprehensive lesion risk threshold, and the digestive tract lesion grade is obtained according to the threshold comparison result, specifically including: Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold to obtain a digestive tract lesion grade; Extracting a first threshold and a second threshold according to the digestive tract comprehensive lesion risk threshold, wherein the first threshold is greater than the second threshold; comparing the digestive tract comprehensive lesion risk index with the first threshold and the second threshold; If the digestive tract comprehensive lesion risk index is greater than the first threshold, the digestive tract lesion level is a severe level; If the digestive tract comprehensive lesion risk index is greater than the second threshold and less than or equal to the first threshold, the digestive tract lesion level is moderate; If the comprehensive digestive tract lesion risk index is less than or equal to the second threshold, the digestive tract lesion level is a mild level.

6. The method for analyzing digestive tract lesions based on gastroscopy results according to claim 5, characterized in that: The step of matching the digestive tract lesion grade with a preset digestive tract lesion grade database, obtaining a corresponding treatment plan and sending the plan to the smart terminal specifically includes: Inputting the digestive tract lesion grade into a preset digestive tract lesion grade database for matching to obtain a corresponding treatment plan; If the digestive tract lesion level is mild, the treatment plan is conventional health care treatment; If the digestive tract lesion is of moderate grade, the treatment plan is to further strengthen the examination; If the gastrointestinal lesion level is severe, the treatment plan is intensive monitoring.

7. A digestive tract lesion analysis system based on gastroscopy results, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises a digestive tract lesion analysis method program based on gastroscopy results, and the digestive tract lesion analysis method program based on gastroscopy results is executed by the processor to implement the following steps: Acquire gastroscopy feature data, and extract esophageal examination feature parameters, stomach examination feature parameters, and duodenum examination feature parameters; Obtaining an upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters; The duodenal examination characteristic parameters are combined with the upper digestive tract lesion risk index to obtain a digestive tract comprehensive lesion risk index; Comparing the digestive tract comprehensive lesion risk index with a preset digestive tract comprehensive lesion risk threshold, and obtaining a digestive tract lesion grade according to the threshold comparison result; The digestive tract lesion grade is matched with a preset digestive tract lesion grade database, and a corresponding treatment plan is obtained and sent to the smart terminal.

8. The digestive tract lesion analysis system based on gastroscopy results according to claim 7, characterized in that: The obtaining of gastroscopy characteristic data and the extraction of esophageal examination characteristic parameters, stomach examination characteristic parameters and duodenum examination characteristic parameters specifically include: Extracting esophageal examination characteristic parameters, including esophageal lesion color data, esophageal lesion texture data, and esophageal lesion morphological characteristic data; Extract gastric examination characteristic parameters, including gastric mucosal color data, gastric lesion morphological characteristic data, and gastric motility parameters; Extract duodenal examination characteristic parameters, including lesion morphological characteristic data, lesion smoothness change data and lesion texture characteristic data.

9. The digestive tract lesion analysis system based on gastroscopy results according to claim 8, characterized in that: The step of obtaining the upper digestive tract lesion risk index according to the esophageal examination characteristic parameters and the stomach examination characteristic parameters specifically includes: Calculate the esophageal lesion index according to the esophageal lesion color data, the esophageal lesion texture data and the esophageal lesion morphological feature data; Obtaining a gastric lesion index according to the gastric mucosal color data, gastric lesion morphological characteristic data and gastric peristalsis parameter processing; The upper gastrointestinal lesion risk index is obtained by processing the esophageal lesion index and the gastric lesion index using a preset upper gastrointestinal lesion risk assessment model.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a digestive tract lesion analysis method program based on gastroscopy results. When the digestive tract lesion analysis method program based on gastroscopy results is executed by a processor, the steps of the digestive tract lesion analysis method based on gastroscopy results as described in any one of claims 1 to 6 are implemented.

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