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Application of Artificial Neural Networks in Automatic Cartilage Segmentation


Long, NQ and Jiang, D and Ding, C, Application of Artificial Neural Networks in Automatic Cartilage Segmentation, Proceedings of IWACI2010, 25-27 August, 2010, Suzhou, China, pp. 81-85. ISBN 978-1-4244-6336-7 (2010) [Refereed Conference Paper]

DOI: doi:10.1109/IWACI.2010.5585177


Magnetic resonance imaging of articular cartilage has recently been recognized as the best non-invasive tool to visualize the cartilage morphology, biochemistry and function. In this paper, the challenging issue of automatic determining the cartilage volume is tackled. First, algorithms based on classical segmentation methods such as thresholding, poly-fitting, and average weight calculating are combined and tailored to develop a clustered segmentation method. Second, artificial neural network (ANN) is applied to improve the developed method by better coping with the nonlinearity and unidentified MRI image noises. This ANN is then applied with the active contour models (Snake) to provide the desirable outcome. Computational examples are given to justify our analysis and demonstrate the proposed method.

Item Details

Item Type:Refereed Conference Paper
Keywords:Cartilage Segmenttation, Neural Network
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Image processing
Objective Division:Health
Objective Group:Clinical health
Objective Field:Clinical health not elsewhere classified
UTAS Author:Long, NQ (Mr Quang Long Ngo)
UTAS Author:Jiang, D (Dr Danchi Jiang)
UTAS Author:Ding, C (Professor Chang-Hai Ding)
ID Code:65074
Year Published:2010
Deposited By:Engineering
Deposited On:2010-09-29
Last Modified:2012-03-05

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