Melanoma lesion detection and segmentation using deep region based convolutional neural network and fuzzy C-means clustering.

Journal: International journal of medical informatics
Published Date:

Abstract

OBJECTIVE: Melanoma is a dangerous form of the skin cancer responsible for thousands of deaths every year. Early detection of melanoma is possible through visual inspection of pigmented lesions over the skin, treated with simple excision of the cancerous cells. However, due to the limited availability of dermatologists, the visual inspection alone has the limited and variable accuracy that leads the patient to undergo a series of biopsies and complicates the treatment. In this work, a deep learning method is proposed for automated Melanoma region segmentation using dermoscopic images to overcome the challenges of automated Melanoma region segmentation within dermoscopic images.

Authors

  • Nudrat Nida
    Department of Computer Engineering, University of Engineering & Technology, Taxila, Pakistan. Electronic address: 16F-PHD-CP-53@uettaxila.edu.pk.
  • Aun Irtaza
    Department of Computer Science, University of Engineering & Technology, Taxila, Pakistan. Electronic address: aun.irtaza@uettaxila.edu.pk.
  • Ali Javed
    Department of Software Engineering, University of Engineering & Technology, Taxila, Pakistan. Electronic address: ali.javed@uettaxila.edu.pk.
  • Muhammad Haroon Yousaf
    Department of Computer Engineering, University of Engineering & Technology, Taxila, Pakistan. Electronic address: haroon.yousaf@uettaxila.edu.pk.
  • Muhammad Tariq Mahmood
    School of Computer Science and Engineering, Korea University of Technology and Education, 1600, Chungjeol-ro, Byeongcheon-myeon, Dongnam-gu, Cheonan-si, Chungcheongnam-do, 31253, Republic of Korea. Electronic address: tariq@koreatech.ac.kr.