Tuberculosis diagnosis method based on deep-learning

A deep learning and inspection method technology, applied in the field of tuberculosis inspection, can solve problems such as trouble, eye fatigue, and difficulty in distinguishing the shape of tuberculosis bacteria, and achieve the effect of reducing inspection errors and easy operation

Pending Publication Date: 2019-07-09
株式会社璘实拍虒
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  • Claims
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AI Technical Summary

Problems solved by technology

[0006] This kind of sputum smear test is widely used because the experimental operation is relatively simple and the result can be judged in a short time. However, the proficiency of the inspector will affect the accuracy of the test result. Therefore, whether there is tuberculosis and the treatment process encountered difficulties in predicting
[0007] Moreover, with respect to the microscope usually used for sputum smear examination, the examiner needs to place a glass slide (slide) on the stage every time an examination is performed, while changing the position and focus of the slide glass, It is troublesome to confirm the presence of tuberculosis one by one with the naked eye, and it is necessary to replace other slides after the inspection
[0008] In o

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  • Tuberculosis diagnosis method based on deep-learning
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Embodiment Construction

[0029] Hereinafter, the present invention will be described in detail with reference to the drawings so that those skilled in the art to which the present invention pertains can easily implement the embodiments of the present invention. However, the present invention can be realized in various forms, and is not limited to the examples described in the present invention. In order to clearly describe the present invention, parts irrelevant to the description in the drawings are omitted, and similar symbols are used for similar components throughout the specification.

[0030] The tuberculosis inspection method based on deep learning according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0031] figure 1 It is an image shooting device installed in the Tuberculosis Research Institute of an embodiment of the present invention, figure 2 It is a focus calculation method of each object according to an embodiment of the pr...

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Abstract

A tuberculosis diagnosis method based on deep-learning of the present invention comprises: a step of acquiring an image from a sputum smear slide made for training by using image capturing equipment;a learning step of learning a deep-learning model to be used to determine tuberculosis by using the acquired image; a verification step of verifying accuracy in the deep-learning model learned throughthe learning step; a step of determining negative or positive for tuberculosis by using a weighted value of the deep-learning model learned through the learning step and the verification step; and adisplaying step of providing, to a user, a test result made through the tuberculosis determination step by displaying the test result on a monitor.

Description

technical field [0001] The present invention relates to a tuberculosis inspection method. In more detail, the present invention relates to a tuberculosis inspection method based on deep learning that can reduce inspection errors through the automation of sputum smear tuberculosis inspection. Background technique [0002] Although the standard of living and medical care has been improved, the number of tuberculosis patients continues to increase. According to the World Health Organization (WHO), the number of tuberculosis infections in 2013 was 9 million, of which 1.5 million South Korea also showed a trend of increasing tuberculosis patients and ranked first among OECD countries. [0003] Diagnosis methods for tuberculosis include sputum smear examination, sputum culture examination, drug sensitivity test, chest radiography and tuberculin skin test (Tuberculin Skin Test, TST). [0004] Among them, sputum smear examination and culture method are the most widely used, especia...

Claims

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Application Information

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IPC IPC(8): G16H50/20G16H50/50G06N3/08
CPCG06N3/08G06T2207/20081G06T2207/20084G16H50/20G16H50/50
Inventor 崔明阵金兑映金汶记朴贤佑朴俊浩辛素燕郑海永
Owner 株式会社璘实拍虒
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