Comparison of Different Color Spaces for Abnormality Detection in Breast Thermograms

Breast cancer is one of the most diagnosed cancers in women worldwide. Thermography serves as a potential screening modality for early breast abnormality detection. A breast thermogram is a pseudo-colored RGB image that is obtained using a thermal palette. Different types of thermal palettes can be used for pseudo-coloring breast thermograms and may influence abnormality detection in RGB breast thermograms. Universal color spaces/ color models that are derived from RGB color space can be used to mitigate the influence of the choice of different thermal palettes. In this work, RGB breast thermograms are mapped to five different color spaces (namely YIQ color space, YCbCr color space, XYZ color space, LAB color space, and HSV color space). The performance of an existing novel, non-learning, threshold-based breast abnormality detection methodology using these mapped thermograms is investigated. An exhaustive channel-wise analysis of different color spaces is also explored to study the influence of each color space channel on breast abnormality detection.