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Real-time monitoring method for enteroscope withdrawal time based on random forest algorithm

A random forest algorithm and real-time monitoring technology, applied in the field of medical assistance, can solve problems such as long learning process, many setting parameters, over-fitting, etc., and achieve the effect of improving the quality of colonoscopy examination and ensuring objectivity

Pending Publication Date: 2020-10-13
WUHAN ENDOANGEL MEDICAL TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, its algorithm has too many parameters, the learning process is long, and it is prone to overfitting and stalemate.

Method used

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  • Real-time monitoring method for enteroscope withdrawal time based on random forest algorithm
  • Real-time monitoring method for enteroscope withdrawal time based on random forest algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] S1. Collect endoscopic image data of non-cecum, ileocecum and appendix opening in the intestine;

[0031] S2. Divide and mark the image data of the non-cecum, ileocecum, and appendix opening according to the sequence of colonoscopy examination to obtain a colonoscopy data set;

[0032] S3. Based on the random forest algorithm, construct and train the identification model of the ileocecal part of the colonoscope;

[0033] The S3.1 colonoscopy image data set enhances the image features in the training set through image enhancement technology based on color and texture features;

[0034] Specific enhancements include:

[0035] 1. Color enhancement: use image brightness, saturation, and contrast changes to increase the amount of data;

[0036] 2. Principal component analysis: Calculate the mean and standard deviation according to the three RGB color channels, then calculate the covariance matrix on the entire training set, perform eigendecomposition, and obtain the eigenv...

Embodiment 2

[0044] The difference technology with embodiment one is:

[0045] S4.1 Since the number of colonoscopy video image frames is too high, it is necessary to obtain colonoscopy pictures by drawing frames at equal time intervals, arrange the acquired pictures in chronological order, and input them into the colonoscopy ileocecal recognition model for judgment;

[0046] S4.2 Each decision tree is trained according to its extracted sample set, by generating a series of rules, and then classifying pictures based on these rules;

[0047] S4.3 Synthesize the classification results of each decision tree, vote for each record, and finally judge the location.

Embodiment 3

[0049] The difference technology with embodiment two is:

[0050]In step S4, the final judgment result of whether the ileocecal part or the opening of the appendix is ​​reached is based on the multiple consecutive sub-results returned by the ileocecal part recognition model, and is given after 9 out of 5 analysis, so that the results are fast and accurate It can judge the type of digestive endoscopy in real time, without waiting for the end of the examination to give the result.

[0051] The final judgment result is based on the multiple consecutive sub-judgment results returned by the ileocecal recognition model of the colonoscope, and is given after the analysis of 9 out of 5 (9 out of 5 or 7 out of 4 can be adjusted as needed). The probability of identifying errors, while ensuring that the method can realize the real-time judgment of the ileocecal portion or appendix opening of the colonoscope, without waiting for the end of the inspection to give a judgment.

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Abstract

The invention relates to the technical field of medical assistance, in particular to a real-time monitoring method for enteroscope withdrawal time based on a random forest algorithm, which comprises the following steps of S1, collecting endoscopic image data of intestinal non-cecum, ileocecum and appendix opening, S2, dividing and marking the image data of the non-cecum, the ileocecum and the appendix opening according to the endoscope entering sequence of enteroscopy to obtain an enteroscopy data set, S3, based on a random forest algorithm, constructing and training an enteroscope ileocecum recognition model, and S4, judging whether the current digestive endoscopy video image is an ileocecum or an appendix opening or not, judging that the current digestive endoscopy video image is the ileocecum or the appendix opening, starting endoscope reversing timing until the enteroscope is moved out of the body. According to the method, a random forest algorithm is adopted to train an enteroscope ileocecum model, and the ileocecum or appendix opening at the tail end of the intestine is recognized through the model. Automatic recording and displaying of enteroscope return operation time are achieved, the purpose of reminding an endoscopist is achieved, and enteroscope examination quality is guaranteed.

Description

technical field [0001] The invention relates to the technical field of medical assistance technology, in particular to a method for real-time monitoring of colonoscope retraction time based on random forest algorithm. Background technique [0002] Colonoscopy is one of the important techniques for diagnosis and treatment of lower gastrointestinal diseases such as colorectal polyps and tumors. Among them, the quality control of endoscopy is an important process of colonoscopy. The European Society of Gastrointestinal Endoscopy (ESGE), the Society of Digestive Endoscopy of the Chinese Medical Association, and the American Society of Gastrointestinal Endoscopy (ASGE) issued statements on the quality control of colonoscopy screening in 2012, 2014, and 2015, respectively. Colonoscopy entry time, withdrawal time, adenoma detection rate and other indicators were used as the quality control items of colonoscopy examination. All three guidelines regard the withdrawal time of colono...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G16H30/40A61B1/31A61B1/04
CPCG16H30/40A61B1/31A61B1/04G06F18/24323
Inventor 邹佩江刘奇为胡珊李超
Owner WUHAN ENDOANGEL MEDICAL TECH CO LTD
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