© 2014

Computer Vision Techniques for the Diagnosis of Skin Cancer

  • Jacob Scharcanski
  • M. Emre Celebi
  • Addresses the utilization of computer vision techniques in the diagnosis of skin cancer

  • Contains the state-of-the-art in skin cancer image analysis in a single comprehensive volume

  • Each chapter is contributed by a leading expert in the field


Part of the Series in BioEngineering book series (SERBIOENG)

Table of contents

  1. Front Matter
    Pages i-x
  2. Maryam Sadeghi, Paul Wighton, Tim K. Lee, David McLean, Harvey Lui, M. Stella Atkins
    Pages 1-22
  3. Aurora Sáez, Begoña Acha, Carmen Serrano
    Pages 23-48
  4. Gabriella Fabbrocini, Valerio De Vita, Sara Cacciapuoti, Giuseppe Di Leo, Consolatina Liguori, Alfredo Paolillo et al.
    Pages 71-107
  5. Fengying Xie, Yefen Wu, Zhiguo Jiang, Rusong Meng
    Pages 109-137
  6. Jose Luis García Arroyo, Begoña García Zapirain
    Pages 139-192
  7. Robert Amelard, Jeffrey Glaister, Alexander Wong, David A. Clausi
    Pages 193-219
  8. Jiuai Sun, Zhao Liu, Yi Ding, Melvyn Smith
    Pages 243-265
  9. Yu Zhou, Zhuoyi Song
    Pages 267-282

About this book


The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer.
Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years, dermoscopy has proved valuable in visualizing the morphological structures in pigmented lesions. However, it has also been shown that dermoscopy is difficult to learn and subjective. Newer technologies such as infrared imaging, multispectral imaging, and confocal microscopy, have recently come to the forefront in providing greater diagnostic accuracy. These imaging technologies presented in this book can serve as an adjunct to physicians and  provide automated skin cancer screening. Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.


Computer Vision Medical Computer-aided Diagnonsis Confocal Spectroscopy Dermoscopy Malignant Melanoma Medical Image Anaylsis Multispectral Imaging Skin Cancer Screening Skin Infrared Imaging

Editors and affiliations

  • Jacob Scharcanski
    • 1
  • M. Emre Celebi
    • 2
  1. 1.Federal University of Rio Grande do SulPorto AlegreBrazil
  2. 2.Computer Science dept.Louisiana State University ShreveportShreveportUSA

Bibliographic information

Industry Sectors
Health & Hospitals
Consumer Packaged Goods
Materials & Steel


From the reviews:


“Researchers specializing in applying mathematical principles for generating an accurate computer analysis of dermatoscopic images of pigmented lesions may want to read this book. … The purpose is to provide current information on computer visualization of pigmented skin lesions and skin cancers. The audience is researchers in the field.” (Patricia Wong, Doody’s Book Reviews, February, 2014)