Semi-automatic Segmentation of Fractured Pelvic Bones for Surgical Planning

Abstract

The segmentation of bones and bone fragments in clinical computed tomography datasets is an important first step in order to carry out computer-based surgical planning using patient-specific anatomical models. While semi-automatic and automatic methods have been proposed for the intact pelvic bone, the segmentation of bone fragments in the fractured pelvic bone still is a challenge due to weak boundaries and the diversity of injury patterns. We propose a semi-automatic multi-step segmentation method using bone and fracture gap enhancement filtering and a graph cut based bone fragment separation approach. The key contribution is a technique for automated detection of incorrect bone fragment separation in the case of incomplete pelvic fractures based on fracture gap planes detected in Hessian filtered images. Moreover, we propose a new sheetness measure based on a modified Hessian matrix. Our system is capable of segmenting fragments of complex hip fractures with only minimal user interaction.