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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11784

Title: Automatic Analysis Algorithm of MR Images for Knee Pain Diagnosis
Authors: Juang, D. J.;Chou, F.-P.;Hsu, T.-C.;Huang, H.-W.;Chen, H.-T.;Chung, Yi-Nung
Contributors: 電機工程學系
Keywords: MR images;Combinatorial based kinematic patellar tracking;Edge-constrained wavelet enhancement;Moment preserving segmentation
Date: 2005-11
Issue Date: 2012-07-02T02:08:35Z
Publisher: Southern Taiwan University of Technology, Department of Electrical Engineering
Abstract: Kinematic approaches using MR images have been regarded of more accuracy in knee pain (AKP) detection than stationary approaches. However, the challenge in segmenting femur, patellar and tibia due to the intensity non-uniformity caused by magnetic propagation degradation in MR images, and the strong adhesion of the soft tissue around the knee organs, has restricted the use of kinematic approaches. This paper
proposes a combinatorial based kinematic patellar tracking (CKPT) for AKP detection. The CKPT uses a hybrid approach for extracting knee organs, where an edge-constrained wavelet enhancement followed by moment preserving segmentation is employed for conquering the soft tissue adhesion for extracting the femur and tibia from axial MR images, and a sliding window based moment preserving for resolving the
segmentation difficulty associated with intensity non-uniformity in saggital MR images. The location constraints are then applied for extracting landmark points from femur and patellar, and three inclination angles reflecting patellar position and orientation, during leg movement, are calculated as the measurement of patellar dislocation. The experiment shows that the hybrid approach can accurately extract femur, patellar and tibia. It also demonstrates the prominent of the calculated inclination angles in detecting AKP.
Relation: 2005 CACS Automatic Control Conference, Tainan, Taiwan, Nov 18-19, 2005
Appears in Collections:[電機工程學系] 會議論文

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