Skin Lesion Image Analysis for Melanoma Detection Call for Papers

Call for Papers: 
IEEE Journal of Biomedical Health Informatics Special Issue on 
Skin Lesion Image Analysis for Melanoma Detection

The goals of this special issue are to summarize the state-of-the-art
in both the computerized analysis of skin lesion images, as well as
image acquisition technologies, providing future directions for this
exciting subfield of medical image analysis. The intended audience
includes researchers and practicing clinicians, who are increasingly
using digital analytic tools.

Invasive and in-situ malignant melanoma together comprise one of the
most rapidly increasing cancers in the world. Invasive melanoma alone
has an estimated incidence of 87,110 and of 9,730 deaths in the United
States in 2017. Early diagnosis is critical, as melanoma can be
effectively treated with simple excision if detected early.

In the past, the primary form of diagnosis for melanoma has been
unaided clinical examination, which has limited and variable accuracy,
leading to significant challenges both in the early detection of
disease and the minimization of unnecessary biospies. In recent years,
dermoscopy has improved the diagnostic capability of trained
specialists. However, dermoscopy remains difficult to learn, and
several studies have demonstrated limits of dermoscopy when proper
training is not administered. In addition, even with sufficient
training, analyses remain highly subjective.

Newer imaging technologies such as infrared imaging, multispectral
imaging, and confocal microscopy, have recently come to the forefront
in providing the potential for greater diagnostic accuracy. In
addition, various research studies have been focused on developing
algorithms for the automated analysis of skin lesion
images. Combinations of such technologies have the potential to serve
as adjuncts to physicians, improving clinical management, especially
for patients with a high degree of lesion burden.

This special issue aims to cover all aspects of skin lesion image
analysis. Topics of interest include, but are not limited to:

- Novel and emerging imaging technologies
- Image enhancement
- Image registration
- Image segmentation
- Feature extraction
- Image classification
- Hardware systems

We are particularly interested in studies that make their data sets
and software publicly available.

Please note that new submissions are required to be at least 70%
different from any other publications. For detailed manuscript
preparation/submission instructions, please visit

Guest Editors

M. Emre Celebi
University of Central Arkansas
ecelebi AT uca DOT edu

Noel Codella
IBM T. J. Watson Research Center
nccodell AT us DOT ibm DOT com

Allan Halpern
Memorial Sloan Kettering Cancer Center
halperna AT mskcc DOT org

Dinggang Shen
University of North Carolina, Chapel Hill
dinggang_shen AT med DOT unc DOT edu

Important Dates

Submission of initial manuscripts: October 1, 2017
Initial notifications: December 1, 2017
Submission of revised manuscripts: February 1, 2018
Final notifications: March 1, 2018