Tuberculosis diagnosis method based on deep-learning

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...

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