Automated MR hip bone segmentation

Xia, Ying, Chandra, Shakes, Salvado, Olivier, Fripp, Jurgen, Schwarz, Raphael, Lauer, Lars, Engstrom, Craig and Crozier, Stuart (2011). Automated MR hip bone segmentation. In: International Conference on Digital Image Computing Techniques and Applications (DICTA). International Conference on Digital Image Computing Techniques and Applications (DICTA), Noosa, QLD, Australia, (25-30). 6-8 December 2011. doi:10.1109/DICTA.2011.13

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Author Xia, Ying
Chandra, Shakes
Salvado, Olivier
Fripp, Jurgen
Schwarz, Raphael
Lauer, Lars
Engstrom, Craig
Crozier, Stuart
Title of paper Automated MR hip bone segmentation
Conference name International Conference on Digital Image Computing Techniques and Applications (DICTA)
Conference location Noosa, QLD, Australia
Conference dates 6-8 December 2011
Proceedings title International Conference on Digital Image Computing Techniques and Applications (DICTA)
Journal name Proceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2011
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2011
Sub-type Fully published paper
DOI 10.1109/DICTA.2011.13
ISBN 9781457720062
9780769545882
Start page 25
End page 30
Total pages 6
Collection year 2012
Language eng
Abstract/Summary The accurate segmentation of the bone and articular cartilages from magnetic resonance (MR) images of the hip is important for clinical studies and drug trials into conditions like osteoarthritis. In current studies, segmentations are obtained using time-consuming manual or semi-automatic algorithms which have high inter- and intra-observer variabilities. This paper presents an important step towards obtaining automatic and accurate segmentations of the hip cartilages, namely an approach to automatically segment the bones. The segmentation is performed using three-dimensional active shape models, which are initialized using an affine registration to an atlas. The accuracy and robustness of the approach was experimentally validated using an MR database of weVIBE, weDESS and MEDIC MR images. The (left, right) femoral and acetabular bone segmentation had a median Dice similarity coefficient of (0.921, 0.926) and (0.830, 0.813).
Keyword Osteoarthritis
Bone
Cartilage
Segmentation
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Wed, 04 Apr 2012, 11:51:11 EST by Ms Deborah Brian on behalf of School of Information Technol and Elec Engineering