NDLI: Automated segmentation for patella from lateral knee X-ray images

Content Provider	IEEE Xplore Digital Library
Author	Chen, H.C. Wu, C.H. Lin, C.J. Liu, Y.H. Sun, Y.N.
Copyright Year	2009
Description	Author affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C. (Chen, H.C.; Wu, C.H.; Sun, Y.N.) \|\| Department of Information Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan, R.O.C. (Liu, Y.H.) \|\| Department of Orthopedics, National Cheng Kung University Hospital, National Cheng Kung University, Tainan, Taiwan, R.O.C. (Lin, C.J.)
Abstract	X-ray image segmentation is an important issue in medical image analysis. Due to inconsistent X-ray absorption, the intensities are usually unevenly distributed and noisy in the processed organ, thus the object segmentation becomes difficult. In this paper we propose a new segmentation method for patella from the lateral knee X-ray images based on the active shape model (ASM). At first, a patella shape model is constructed by principal component analysis (PCA) of corresponding landmarks obtained from a set of training shape. As the knee X-ray image usually contains many anatomical structures, we design a strategy based on edge tracing to place the initial shape model as close to the patella boundary as possible. Then, the shape model is deformed and fitted to the patella boundary by using a dual-optimization approach that includes a genetic algorithm (GA) to get the global geometric transform and ASM to deform the shape model iteratively. Consequently, the proposed method can cope with different knee X-ray images and can segment the patella in an automatic procedure. In the experiment, 20 images were tested and promising results are obtained by the proposed method. This method is found useful for the clinical evaluation and biomechanical study of knee.
Starting Page	3553
Ending Page	3556
File Size	448261
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5332588
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Knee X-ray imaging Shape Principal component analysis Solid modeling Deformable models Biomedical imaging Image edge detection Electromagnetic wave absorption
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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