Journal article
LOGISMOS-Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces: Cartilage Segmentation in the Knee Joint
IEEE transactions on medical imaging, Vol.29(12), pp.2023-2037
12/2010
DOI: 10.1109/TMI.2010.2058861
PMCID: PMC3131162
PMID: 20643602
Abstract
A novel method for simultaneous segmentation of multiple interacting surfaces belonging to multiple interacting objects, called LOGISMOS (layered optimal graph image segmentation of multiple objects and surfaces), is reported. The approach is based on the algorithmic incorporation of multiple spatial inter-relationships in a single n-dimensional graph, followed by graph optimization that yields a globally optimal solution. The LOGISMOS method's utility and performance are demonstrated on a bone and cartilage segmentation task in the human knee joint. Although trained on only a relatively small number of nine example images, this system achieved good performance. Judged by dice similarity coefficients (DSC) using a leave-one-out test, DSC values of 0.84 0.04, 0.80 0.04 and 0.80 0.04 were obtained for the femoral, tibial, and patellar regions, respectively. These are excellent DSC values, considering the narrow-sheet character of the cartilage regions. Similarly, low signed mean cartilage thickness errors were obtained when compared to a manually-traced independent standard in 60 randomly selected 3-D MR image datasets from the Osteoarthritis Initiative database-0.11 0.24, 0.05 0.23, and 0.03 0.17 mm for the femoral, tibial, and patellar cartilage thickness, respectively. The average signed surface positioning errors for the six detected surfaces ranged from 0.04 0.12 mm to 0.16 0.22 mm. The reported LOGISMOS framework provides robust and accurate segmentation of the knee joint bone and cartilage surfaces of the femur, tibia, and patella. As a general segmentation tool, the developed framework can be applied to a broad range of multiobject multisurface segmentation problems.
Details
- Title: Subtitle
- LOGISMOS-Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces: Cartilage Segmentation in the Knee Joint
- Creators
- Yin Yin - Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USAXiangmin Zhang - Med. Imaging Applic., Coralville, IA, USARachel Williams - Dept. of Orthopaedics & Rehabilitation, Univ. of Iowa, Iowa City, IA, USAXiaodong Wu - Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USADonald D Anderson - Dept. of Orthopaedics & Rehabilitation, Univ. of Iowa, Iowa City, IA, USAMilan Sonka - Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.29(12), pp.2023-2037
- DOI
- 10.1109/TMI.2010.2058861
- PMID
- 20643602
- PMCID
- PMC3131162
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers
- Language
- English
- Date published
- 12/2010
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Orthopedics and Rehabilitation; Industrial and Systems Engineering; Radiation Oncology; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984040389802771
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