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Journal of Healthcare Engineering
Volume 1 (2010), Issue 1, Pages 27-43
http://dx.doi.org/10.1260/2040-2295.1.1.27
Research Article

Analysis of Breast Thermography Using Fractal Dimension to Establish Possible Difference between Malignant and Benign Patterns

Mahnaz Etehad Tavakol,1,4 Caro Lucas,2 Saeed Sadri,1,4 and E. Y. K. Ng3

1Electrical and Computer Engineering Department, Isfahan University of Technology, Iran
2Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran
3School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore
4Medical Image and Signal Processing Research Center, Isfahan University of Medical Science, Isfahan 81746-73461, Iran

Copyright © 2010 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Early detection of breast cancer by means of thermal imaging has a long and extremely controversial history. Recently, the availability of highly sensitive infrared (IR) cameras which can produce high-resolution diagnostic images of the temperature and vascular changes of breasts, as well as a better knowledge of advanced image processing techniques, has generated a renewed interest. The objective of this study is to investigate fractal analysis of breast thermal images and to develop an algorithm for detecting benignity and malignancy of breast diseases. The study is based on IR images captured by thermal camera, in which the resolution of the results is within the state of the art of IR camera. A total of 7 malignant cases and 8 benign cases have been considered. The breast images were first segmented by fuzzy c-means clustering. Then the first hottest regions for each image were identified and the fractal dimension of those regions was computed. It is shown that the fractal dimension results significantly differ between malignant and benign patterns, suggesting that fractal analysis may potentially improve the reliability of thermography in breast tumor detection.