Dense Pooling layers in Fully Convolutional Network for Skin Lesion Segmentation

• DOI: 10.48550/arxiv.1712.10207
• Publication Date: 2017-01-01
• Authors: Nasr-Esfahani, Eb...; Rafiei, Shima; Jafari, Mohammad H.; Karimi, Nader; Wrobel, James S.; Soroushmehr, S. M...; Samavi, Shadrokh; Najarian, Kayvan
• Keywords: FOS: Computer and information sciences; 03 medical and health sciences; 0302 clinical medicine; Computer Vision and Pattern Recognition (cs.CV); Computer Science - Computer Vision and Pattern Recognition; 3. Good health

One of the essential tasks in medical image analysis is segmentation and accurate detection of borders. Lesion segmentation in skin images is an essential step in the computerized detection of skin cancer. However, many of the state-of-the-art segmentation methods have deficiencies in their border detection phase. In this paper, a new class of fully convolutional network is proposed, with new dense pooling layers for segmentation of lesion regions in skin images. This network leads to highly accurate segmentation of lesions on skin lesion datasets which outperforms state-of-the-art algorithms in the skin lesion segmentation.