Dense pooling layers in fully convolutional network for skin lesion segmentation.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Published Date:

Abstract

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.

Authors

  • Ebrahim Nasr-Esfahani
  • Shima Rafiei
  • Mohammad H Jafari
    Department of Electrical Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
  • Nader Karimi
  • James S Wrobel
    Department of Internal Medicine, University of Michigan, Ann Arbor, 48109, USA.
  • Shadrokh Samavi
  • S M Reza Soroushmehr