1. 트랜스포머 블록과 윤곽선 디코더를 활용한 딥러닝 기반의 피부 병변 분할 방법.
- Author
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김지훈, 박경리, 김해문, and 문영식
- Subjects
SKIN cancer ,DEEP learning ,DERMOSCOPY ,CANCER diagnosis ,EDGES (Geometry) - Abstract
Specialists diagnose skin cancer using a dermatoscopy to detect skin cancer as early as possible, but it is difficult to determine accurate skin lesions because skin lesions have various shapes. Recently, the skin lesion segmentation method using deep learning, which has shown high performance, has a problem in segmenting skin lesions because the boundary between healthy skin and skin lesions is not clear. To solve these issues, the proposed method constructs a transformer block to effectively segment the skin lesion, and constructs an edge decoder for each layer of the network to segment the skin lesion in detail. Experiment results have shown that the proposed method achieves a performance improvement of 0.041 ~ 0.071 for Dic Coefficient and 0.062 ~ 0.112 for Jaccard Index, compared with the previous method. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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