Journal article
EM Segmentation of the Distal Femur and Proximal Tibia: A High-Throughput Approach to Anatomic Surface Generation
Annals of biomedical engineering, Vol.39(5), pp.1555-1562
05/2011
DOI: 10.1007/s10439-010-0244-7
PMID: 21222162
Abstract
Fully automated segmentation of computed tomography (CT) images remains a challenge for musculoskeletal researchers. The surfaces generated from image segmentations are valuable for surgical evaluation and planning. Previously, we demonstrated the expectation maximization (EM) algorithm as a semi-automated method of bone segmentation from CT images. In this work, we improve upon the methodology of probability map generation and demonstrate extended applicability of EM-based segmentation to the distal femur and proximal tibia using 72 CT image sets. We also compare the resulting EM segmentations to manual tracings using overlap metrics and time. In the case of the distal femur, the resulting quality metrics had mean values of 0.91 and 0.95 for the Jaccard and Dice metrics, respectively. For the proximal tibia, the Jaccard and Dice metrics were 0.90 and 0.95, respectively. The EM segmentation method was 8 times faster than the average manual segmentation and required less than 4% of the human rater time. Overall, the EM algorithm offers reliable image segmentations with an increased efficiency in comparison to manual segmentation techniques.
Details
- Title: Subtitle
- EM Segmentation of the Distal Femur and Proximal Tibia: A High-Throughput Approach to Anatomic Surface Generation
- Creators
- Austin Ramme - Center for Computer-Aided Design The University of Iowa Iowa City IA USAAmy Criswell - Center for Computer-Aided Design The University of Iowa Iowa City IA USABrian Wolf - Department of Orthopaedics and Rehabilitation The University of Iowa Iowa City IA USAVincent Magnotta - Department of Radiology The University of Iowa Iowa City IA USANicole Grosland - Department of Orthopaedics and Rehabilitation The University of Iowa Iowa City IA USA
- Resource Type
- Journal article
- Publication Details
- Annals of biomedical engineering, Vol.39(5), pp.1555-1562
- DOI
- 10.1007/s10439-010-0244-7
- PMID
- 21222162
- NLM abbreviation
- Ann Biomed Eng
- ISSN
- 0090-6964
- eISSN
- 1573-9686
- Publisher
- Springer US; Boston
- Language
- English
- Date published
- 05/2011
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Psychiatry; Iowa Neuroscience Institute; Orthopedics and Rehabilitation; Physical Therapy and Rehabilitation Science; Injury Prevention Research Center
- Record Identifier
- 9984040290702771
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