DocumentCode :
2998107
Title :
Automated MR Hip Bone Segmentation
Author :
Xia, Ying ; Chandra, Shakes ; Salvado, Olivier ; Fripp, Jurgen ; Schwarz, Raphael ; Lauer, Lars ; Engstrom, Craig ; Crozier, Stuart
Author_Institution :
Australian e-Health Res. Centre, CSIRO ICT, Brisbane, QLD, Australia
fYear :
2011
fDate :
6-8 Dec. 2011
Firstpage :
25
Lastpage :
30
Abstract :
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 we VIBE, we DESS and MEDIC MR images. The (left, right) femoral and ace tabular bone segmentation had a median Dice similarity coefficient of (0.921, 0.926) and (0.830, 0.813).
Keywords :
affine transforms; biomedical MRI; bone; diseases; drugs; image registration; image segmentation; medical image processing; solid modelling; MEDIC MR images; MR database; accurate segmentations; ace tabular bone segmentation; affine registration; articular cartilages; automated MR hip bone segmentation; automatic segmentations; clinical study; drug trials; femoral tabular bone segmentation; hip cartilages; inter-observer variability; intra-observer variability; magnetic resonance images; median dice similarity coefficient; osteoarthritis; semiautomatic algorithms; three-dimensional active shape models; time-consuming manual algorithms; weDESS MR images; weVIBE MR images; Biomedical imaging; Bones; Computed tomography; Hip; Image segmentation; Joints; Shape; bone; cartilage; osteoarthritis; segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Image Computing Techniques and Applications (DICTA), 2011 International Conference on
Conference_Location :
Noosa, QLD
Print_ISBN :
978-1-4577-2006-2
Type :
conf
DOI :
10.1109/DICTA.2011.13
Filename :
6128655
Link To Document :
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