Book chapter
Simultaneous Segmentation of Multiple Closed Surfaces Using Optimal Graph Searching
Information Processing in Medical Imaging, pp.406-417
Lecture Notes in Computer Science, Springer Berlin Heidelberg
2005
DOI: 10.1007/11505730_34
Abstract
This paper presents a general graph-theoretic technique for simultaneously segmenting multiple closed surfaces in volumetric images, which employs a novel graph-construction scheme based on triangulated surface meshes obtained from a topological presegmentation. The method utilizes an efficient graph-cut algorithm that guarantees global optimality of the solution under given cost functions and geometric constraints. The method’s applicability to difficult biomedical image analysis problems was demonstrated in a case study of co-segmenting the bone and cartilage surfaces in 3-D magnetic resonance (MR) images of human ankles. The results of our automated segmentation were validated against manual tracings in 55 randomly selected image slices. Highly accurate segmentation results were obtained, with signed surface positioning errors for the bone and cartilage surfaces being 0.02±0.11mm and 0.17±0.12mm, respectively.
Details
- Title: Subtitle
- Simultaneous Segmentation of Multiple Closed Surfaces Using Optimal Graph Searching
- Creators
- Kang Li - Carnegie Mellon UniversitySteven Millington - Frank Stronach Institute, Graz, Austria#TAB#Xiaodong Wu - University of IowaDanny Z Chen - University of Notre DameMilan Sonka - University of Iowa
- Resource Type
- Book chapter
- Publication Details
- Information Processing in Medical Imaging, pp.406-417
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/11505730_34
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Language
- English
- Date published
- 2005
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186688502771
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