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A kind of abnormal urine red blood cell classification statistical method and system

A technology of classification statistics and red blood cells, which is applied in the field of artificial intelligence-assisted medical examination, can solve the problems of accurate classification and statistics of abnormal urine red blood cells, cannot effectively reduce the workload of professional doctors, and cannot effectively relieve the pressure of physical examination of kidney disease patients, so as to achieve accurate identification Effects with Categorical Statistics

Active Publication Date: 2021-02-26
TAIYUAN UNIV OF TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, it is difficult to accurately classify and count abnormal urine red blood cells based only on microscope image data and traditional digital image processing algorithms, and thus cannot effectively reduce the workload of professional physicians, and cannot effectively relieve the pressure of physical examination for kidney disease patients in areas where medical resources are scarce.

Method used

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  • A kind of abnormal urine red blood cell classification statistical method and system
  • A kind of abnormal urine red blood cell classification statistical method and system
  • A kind of abnormal urine red blood cell classification statistical method and system

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Embodiment Construction

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, rather than All the embodiments; based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative work all belong to the protection scope of the present invention.

[0042] Such as figure 1 As shown, the embodiment of the present invention provides a kind of abnormal urine red blood cell classification statistics method, comprises the following steps:

[0043] S1. Collect the microscope zoom video of the sample through the video capture module.

[0044] In the embodiment of the present invention, the zoom video of the microscope is recorded by the video acquisition module. Su...

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Abstract

The invention belongs to the technical field of artificial intelligence-assisted medical examination, and discloses a method and system for classification and statistics of abnormal urine red blood cells. Malformed urine red blood cells are identified on the highest frame, and multiple deformed urine red blood cell zoom videos are segmented; S3. Using a deep multi-instance learning algorithm to predict the probability of each frame in each deformed urine red blood cell zoom video under different classifications, S4. The classification and quantity statistics of malformed urine red blood cells are realized through the priority principle of target key frame. The invention can accurately detect and classify and count the deformed urine red blood cells in the sample, the statistical method is accurate and reliable, and can be applied to the field of urine sample detection.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence-assisted medical examination, and specifically relates to a method of using the zoom video of a urine sample of a kidney disease patient under a microscope as analysis data, and combining with a deep multi-instance learning algorithm to classify abnormal urine red blood cells in the urine sample Methods of identification and quantification. Background technique [0002] Patients with kidney disease are often accompanied by occult blood in urine and hematuria. Under the microscope, there are a large number of deformed urine red blood cells caused by the extrusion of glomerulus and other tissues in the urine samples of patients with kidney disease. The abnormal type and quantity of urinary red blood cells can more accurately reflect the type and degree of renal lesions. Therefore, the classification and statistics of abnormal urinary red blood cells in urine samples of patients with ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06K9/62G06K9/00
CPCG06T7/0012G06T2207/10016G06T2207/10056G06T2207/20081G06T2207/20084G06T2207/10148G06T2207/30024G06V20/695G06V20/698G06V20/49G06V20/46G06V2201/03G06F18/24
Inventor 李明李心宇岳俊宏郝芳崔丽涓
Owner TAIYUAN UNIV OF TECH
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