Automated blood vessel extraction in two-dimensional breast thermography

In this paper, we present an automated algorithm for detection of blood vessels in 2D-thermographic images for breast cancer screening. Vessel extraction from breast thermal images help in the classification of malignancy as cancer causes increased blood flow at warmer temperatures, additional vessel formation and tortuosity of vessels feeding the cancerous growth. The proposed algorithm uses three enhanced images to detect possible vessel regions based on their intensity and shape. The final vessel detection combines these three outputs. The algorithm does not depend on the variation of pixel intensity in the images but only depends on the relative variation unlike many standard algorithms. On a dataset of over 40 subjects with high-resolution thermographic images, we are able to extract the vessels accurately with elimination of diffused heat regions. Future studies would involve extracting features from the detected vessels and using these features for classification of malignancy.