Detecting abnormality in medical images with thermal and RGB images

Abstract

Medical abnormalities in human body are often reflected by raise in temperature at various areas in the body. With the requirement of reliable non-invasive on the increase Infrared Thermal Image is an effective aiding in monitoring and diagnosing medical abnormalities. Existing research has applied Infrared Thermal Image effectively for various medical conditions like breast cancer screening, diabetes and peripheral vascular disorder, Risk Assessment and Treatment Monitoring. Thermal Image cameras are capable of capturing the body temperature variations, these temperature variations can lead to significant diagnosis in several areas ranging from simple flu caused by influenza virus to several conditions like diabetes, eye syndrome and thyroid to name a few. Heat distribution captured from Infrared Thermal Image by thermal cameras like Forward Looking Infrared Imaging (FLIR) with a sensitivity range of 0.10C and wide temperature ranging from - 100C to +1000C can produce good thermal images. This research suggests a non-expensive and non-obtrusive diagnostic procedure which utilizes thermal imaging for unexplored areas of applying thermal imaging and the possibility of extracting thermal variations with RGB images. To achieve the objective various image processing techniques like image preprocessing, selecting the Region of Interest (ROI), extraction by region segmentation, selective feature extraction and finally suitable classification of the relevant application selection are adopted. Results of the proposed method for detecting abnormality have been validated based on the temperature map histogram comparison from thermal image.