Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/55874
Type: Conference paper
Title: Development of semi-automatic segmentation methods for measuring tibial cartilage volume.
Author: Cheong, J.
Suter, D.
Cicuttini, F.
Citation: Proceedings of Digital Image Computing: Techniques and Applications, held in Cairns, Queensland, Australia, 2005: pp.45-52
Publisher: IEEE
Publisher Place: Online
Issue Date: 2005
ISBN: 0769524672
Conference Name: Digital Image Computing: Techniques and Applications (2005 : Cairns, Australia)
Statement of
Responsibility: 
James Cheong, David Suter and Flavia Cicuttini
Abstract: Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the coming years. Currently, there is strong interest in developing a fully automated cartilage area/volume measurement method in the medical field to assist both pharmaceutical companies and medical professions in researching the disease. This paper describes the development of two different semi-automatic methods for segmenting and measuring human knee cartilage volume from magnetic resonance imaging (MRI) scans. Two different approaches were adopted, a data driven segmentation technique using directional Canny filters and a model based segmentation method using an improved Active Shape Model (ASM) scheme. The cartilage volume obtained using each method was benchmarked against the current "gold standard" (cartilage volume from manual segmentation).
RMID: 0020094166
Description (link): http://dx.doi.org/10.1109/DICTA.2005.26
Appears in Collections:Computer Science publications

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