![Sample our Computer Science journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5928/TOC-Subject-Sample-2021-Computer-Science.jpg"})
Abstract
Changes of the cartilage morphology over time can tell the progression of osteoarthritis (OA) and show particular promise for evaluating the efficacy of disease-modifying OA drugs. Hence, cartilage matching is required prior to cartilage morphology comparison. An accurate cartilage matching allows one to ensure longitudinal focal and local changes of cartilage morphology due to OA. The method described in this article meets this need. The proposed method consists of three steps. First, the knee femur surfaces are aligned, using the principal axes transformation to correct for different knee joint positions and orientations in the magnetic resonance (MR) scanner. Second, we present a global registration algorithm based on Lipschitz optimization theory for accurately identifying the corresponding points of the knee femur surface. Third, the rigid transformation of the knee femur surface registration is applied to the cartilage surface. Our registration algorithm is efficient and robust, and its performance is evaluated on MR images of pig knees.
Keywords:
Acknowledgments
The authors thank the anonymous reviewer for constructive suggestions. This study is supported by the National Natural Science Foundation of China under Grant Nos 61073124, 81071191, and 60831003; the Nature Science Foundation of Shandong Province of China (No. Q2008G07); the Development Project of Science and Technology in Weihai City; the State key Laboratory of Robotics and System (SKLRS-2009-ZD-03); and the Project under Grant HIT. NSRIF. 2009149.