  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.
