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Application of Artificial Neural Networks in Automatic Cartilage Segmentation

Version 2 2024-09-17, 02:02
Version 1 2023-05-23, 04:58
conference contribution
posted on 2024-09-17, 02:02 authored by NQ Long, D Jiang, Chang-Hai DingChang-Hai Ding
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.

History

Publication title

Proceedings of IWACI2010

Volume

13

Editors

Yuhui Shi and Jun Wang

Pagination

81-85

ISBN

978-1-4244-6336-7

Department/School

Engineering, Menzies Institute for Medical Research

Publisher

IEEE

Publication status

  • Published

Place of publication

Suzhou, China

Event title

International Workshop on Advanced Computational Intelligence

Event Venue

Suzhou, China

Date of Event (Start Date)

2010-08-25

Date of Event (End Date)

2010-08-27

Socio-economic Objectives

200199 Clinical health not elsewhere classified

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