A Hybrid Framework to Evaluate Breast Abnormality Using Infrared Thermal Images

Medical image assessment is an essential practice in most of the disease identification events. A recent imaging procedure, infrared thermal imaging, has attracted wide consumers due to its noninvasive nature, cost, and accuracy. This paper considers the inspection of breast malignancy. This paper presents a hybrid framework with a heuristic algorithm-driven preprocessing practice and a semi/fully automated postprocessing. The result of the proposed technique is also validated against other existing segmentation methods.