Title
3D statistical shape models to embed spatial relationship information
Abstract
This paper presents the creation of 3D statistical shape models of the knee bones and their use to embed information into a segmentation system for MRIs of the knee. We propose utilising the strong spatial relationship between the cartilages and the bones in the knee by embedding this information into the created models. This information can then be used to automate the initialisation of segmentation algorithms for the cartilages. The approach used to automatically generate the 3D statistical shape models of the bones is based on the point distribution model optimisation framework of Davies. Our implementation of this scheme uses a parameterized surface extraction algorithm, which is used as the basis for the optimisation scheme that automatically creates the 3D statistical shape models. The current approach is illustrated by generating 3D statistical shape models of the patella, tibia and femoral bones from a segmented database of the knee. The use of these models to embed spatial relationship information to aid in the automation of segmentation algorithms for the cartilages is then illustrated.
Year
DOI
Venue
2005
10.1007/11569541_7
CVBIA
Keywords
Field
DocType
knee bone,segmentation algorithm,statistical shape model,segmentation system,embed information,embed spatial relationship information,optimisation scheme,point distribution model optimisation,current approach,strong spatial relationship,mri,point distribution model,spatial relationships,in vivo,segmentation
Computer vision,Point distribution model,Active shape model,Parameterized complexity,Embedding,Pattern recognition,Computer science,Segmentation,Spatial relationship,Automation,Knee Joint,Artificial intelligence
Conference
Volume
ISSN
ISBN
3765
0302-9743
3-540-29411-2
Citations 
PageRank 
References 
7
0.52
9
Authors
6
Name
Order
Citations
PageRank
Jurgen Fripp135444.54
Pierrick Bourgeat220733.49
Andrea J. U. Mewes3674.84
Simon K. Warfield42825229.11
Stuart Crozier513014.02
Sébastien Ourselin62499237.61