Melanoma-Nevus Discrimination Based on Image Statistics in Few Spectral Channels

Authors

  • Aivars Lorencs Institute of Electronics and Computer Science
  • Juris Sinica-Sinavskis Institute of Electronics and Computer Science
  • Dainis Jakovels Institute of Atomic Physics and Spectroscopy, University of Latvia
  • Ints Mednieks Institute of Electronics and Computer Science

DOI:

https://doi.org/10.5755/j01.eie.22.2.12173

Keywords:

Image classification, biomedical optical imaging, multispectral imaging, melanoma detection.

Abstract

The purpose of this paper is to offer a method for discrimination of cutaneous melanoma from benign nevus, founded on analysis of skin lesion image. At the core of method is calculation of mean and standard deviation of pixel optical density values for a few narrow spectral bands. Calculated values are compared with discriminating thresholds derived from a set of images of benign nevi and melanomas with known diagnosis. Classification is done applying weighted majority rule to results of thresholding. Verification against the available multispectral images of 32 melanomas and 94 benign nevi has shown that the method using three spectral bands provided zero false negative and four false positive melanoma detections. The proposed classifier is characterized by high sensitivity and specificity concerning statistical point estimates whereas its possible technical implementation is fairly simple. The proposed method may be instrumental for designing low cost diagnostic equipment to be used in primary care that is important for early detection of cutaneous melanoma.

DOI: http://dx.doi.org/10.5755/j01.eie.22.2.12173

Downloads

Published

2016-03-30

How to Cite

Lorencs, A., Sinica-Sinavskis, J., Jakovels, D., & Mednieks, I. (2016). Melanoma-Nevus Discrimination Based on Image Statistics in Few Spectral Channels. Elektronika Ir Elektrotechnika, 22(2), 66-72. https://doi.org/10.5755/j01.eie.22.2.12173

Issue

Vol. 22 No. 2 (2016)

Section

SYSTEM ENGINEERING, COMPUTER TECHNOLOGY

License

The copyright for the paper in this journal is retained by the author(s) with the first publication right granted to the journal. The authors agree to the Creative Commons Attribution 4.0 (CC BY 4.0) agreement under which the paper in the Journal is licensed.

By virtue of their appearance in this open access journal, papers are free to use with proper attribution in educational and other non-commercial settings with an acknowledgement of the initial publication in the journal.