An integrated method for hemorrhage segmentation from brain CT Imaging

This paper presents an integrated segmentation method which combines the features of Fuzzy C-Mean (FCM) clustering and region-based active contour method. In the proposed method, FCM clustering is used to initialize the contour around the hemorrhagic region and then region-based active contour method propagates the initial contour towards the hemorrhage boundaries. Further, the FCM clustering is also used to estimate the contour propagation controlling parameters adaptively from the given image. The region-based active contour method uses the intensity information in the local regions as against the global regions in the traditional region-based active contour methods to guide the contour motion. The effectiveness of the proposed method is tested on the dataset of total 100 hemorrhagic brain CT images of 20 patients and the results are compared with region growing, FCM clustering and Chan & Vese methods. The proposed method yields the higher average values of the similarity indices namely sensitivity, specificity, accuracy and overlap metric as 79.93%, 99.10%, 84.83% and 88.84% respectively.