Hierarchical Approach to Detect Fractures in CT DICOM Images

Abstract

This paper deals with the identification of fractures in CT scan images. A large amount of significant and critical information are normally stored in medical data. Highly efficient and automated computational methods are needed to process and analyze all available data in order to help the physician in diagnosis, decisions and treatment planning. Each CT scan includes a large number of slices. In this paper, a new hierarchical segmentation algorithm is applied to all slices; it automatically extracts the bone structures using HMRF_EM segmentation method. The template-matching technique is employed to extract the affected portion. This new approach is experimented with eight patients’ data and validated by radiologists. The performance of the work is analyzed and compared with recent works using sensitivity, specificity and accuracy.