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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2021.7
- 수록면
- 196 - 196 (1page)
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The development of deep learning has shown outstanding performance in image analysis, and it has been accelerating the attempt to apply the technique to detect the pathological lesion automatically from the whole slide image (WSI) in the non-clinical study, as well as clinical study. We applied three deep learning-based algorithms including Mask R-CNN, DeepLab, and YOLO to detect mononuclear cell infiltration in SD rat liver which is one of the toxicological evidence in a non-clinical study. The lesion classified into two subtypes, lymphocytes and histiocytes infiltration, according to distinct features, therefore, trained separately. Total 4,191 tile images including the lesion were obtained from 44 WSIs for the analysis. The pathological lesions were labeled by VGG annotator 2.0.1.0, and the procedure that related to AI method, including train, validation, and test, was conducted by Tensor flow 2.1.0 powered by NVIDA 2080 Ti GPU. The dataset was divided with the ratio 7: 2: 1 using train_t ... 전체 초록 보기
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