Segmentation of knee joints in x-ray images using decomposition-based sweeping and graph search
Jian Mu, Xiaomin Liu, Shuang Luan, Philip H. Heintz, Gary W. Mlady, Danny Z. Chen · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2011
Plain radiography (i.e., X-ray imaging) provides an effective and economical imaging modality for diagnosing knee illnesses and injuries. Automatically segmenting and analyzing knee radiographs is a challenging problem. In this paper, we present a new approach for accurately segmenting the knee joint in X-ray images. We first use the Gaussian high-pass filter to remove homogeneous regions which are unlikely to appear on bone contours. We then presegment the bones and develop a novel decomposition-based sweeping algorithm for extracting bone contour topology from the filtered skeletonized images. Our sweeping algorithm decomposes the bone structures into several relatively simple components and deals with each component separately based on its geometric characteristics using a sweeping strategy. Utilizing the presegmentation, we construct a graph to model the bone topology and apply an optimal graph search algorithm to optimize the segmentation results (with respect to our cost function defined on the bone boundaries). Our segmented results match well with the manual tracing results by radiologists. Our segmentation approach can be a valuable tool for assisting radiologists and X-ray technologists in clinical practice and training.