Wheal detection from skin prick test images using normalized-cuts and region selection
Skin prick test is a common diagnosis method for allergic diseases. The test causes a controlled allergic response and provokes a wheal on the skin, whose size and shape change depending on the sensitivity of a patient against a specific allergen. The physical size of the wheal can be estimated from images acquired by digital cameras, which requires segmentation of the wheal from the captured SPT images. In this paper, we propose a new method for wheal detection from skin prick test images. The proposed method operates on localized images using a set of calibration marks and a perspective transformation. An initial segmentation of the localized SPT image is performed using normalized cuts to identify coherent regions in the image. The segmented region containing the wheal is selected by formulating an optimization problem to identify the segment with distinctive color, texture, and shape attributes. Our experiments conducted on images acquired from 50 different patients show the performance of the proposed wheal detection algorithm.