Title: An approach to identify lesion in infrared breast thermography images using segmentation and fractal analysis
Authors: A. Lavanya
Addresses: School of Electronic, Electrical and Computer Engineering, University of Birmingham, Edgbaston, Birmingham, West Midlands, B15 2TT, UK
Abstract: Breast thermography as a clinical diagnostic procedure is used to measure the heat coming from the body that provides information based on heat patterns that are strongly indicative of breast abnormality. In this study, an attempt is made to segment hottest regions for detecting region of interest in the infrared breast thermal images using particle swarm optimisation and further with k-means cluster segmentation. Thermography images having different pathologies such as fibrocystic, ductal carcinoma, inflammatory cancer and angiogenesis. Segmentation of breast hot region is performed after removing non-breast region by multiplying original image and ground truth mask. Left and right breast regions are separated by cropping. Segmentation of images based on particle swarm optimisation for determining the threshold level and further k-means cluster is used to estimate the class prototypes indicated by the dense groupings. The differences between cancerous and non-cancerous cases are identified from segmented images using fractal measures.
Keywords: breast thermography; breast image analysis; particle swarm optimisation; PSO; k-means clustering; fractal analysis; lesion identification; breast cancer; infrared thermography; image segmentation; thermal images; fibrocystic; ductal carcinoma; inflammatory cancer; angiogenesis.
International Journal of Biomedical Engineering and Technology, 2015 Vol.19 No.3, pp.220 - 229
Received: 17 Feb 2015
Accepted: 04 Jun 2015
Published online: 11 Nov 2015 *