The invention discloses a medical image
lesion segmentation method and
system for a
radiology department, and relates to the field of medical images. A bone
mask and a bone boundary probability graph are generated by constructing multi-window input of a brain window, a subdural window and a bone window and utilizing a
bone tissue segmentation network, and feature suppression
processing and boundary enhancement
processing are introduced in an
encoder stage and a decoding stage respectively so as to weaken the influence of high-density artifacts in a bone region and strengthen boundary expression of a bone attachment region. And further executing probability correction based on a bone
mask on the initial hemorrhage probability graph, reducing bone region
false detection, and obtaining an accurate cerebral hemorrhage segmentation result. The
system comprises an image access module, a multi-window construction module, a bone prior generation module, a cerebral hemorrhage segmentation module, a probability correction module and a clinical quantification module, and can output structured indexes such as hemorrhage volume,
mass center and
diffusion direction. According to the method, the problems of bone sticking
false detection, fuzzy edge, small-size focus missing detection and the like are solved, and the accuracy of automatic cerebral hemorrhage segmentation is remarkably improved.