Current Result Document :
| 한글제목(Korean Title) |
딥 러닝을 사용한 X선 영상의 폐 질환 분류 |
| 영문제목(English Title) |
Lung Diseases Classification on X-Ray images using Deep Learning |
| 저자(Author) |
김성엽
림빈보니카
이성진
마오마카라
홍민
Sungyeup Kim
Beanbonyka Rim
Sungjin Lee
Makara Mao
and Min Hong
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| 원문수록처(Citation) |
VOL 23 NO. 01 PP. 0203 ~ 0204 (2022. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Lung disease is one of the most causes of death in the world such as pneumonia, and pneumothorax. Chest X-Ray images are scanned to diagnosis lung diseases in the early stage. The computer-aided diagnostic systems (CADs) are used to assist doctors on chest X-Ray images earlier and easier. Therefore, in this paper, we proposed a deep learning approach to classify lung diseases into pneumonia, pneumothorax, and normal. This classification would help to improve the performance of CADs for doctors to diagnosis on X-Ray images more precisely. We exploited EfficientNet-V2-M model to classify lung diseases on the NIH dataset and achieved an accuracy, sensitivity, and specificity of 82.00%, 80.60%, and 92.12% on validation set, respectively.
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| 키워드(Keyword) |
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