Conference proceeding
Optimal graph search based image segmentation for objects with complex topologies
Proceedings of SPIE, Vol.7259(1), pp.725915-7259110
Medical Imaging 2009: Image Processing
02/26/2009
DOI: 10.1117/12.811704
Abstract
Segmenting objects with complicated topologies in 3D images is a challenging problem in medical image processing, especially for objects with multiple interrelated surfaces. In this paper, we extend a graph search based technique to simultaneously identifying multiple interrelated surfaces for objects that have complex topologies (e.g., with tree-like structures) in 3D. We first perform a pre-segmentation on the input image to obtain basic information of the objects' topologies. Based on the initial pre-segmentation, the original image is resampled along judiciously determined directions to produce a set of vectors of voxels (called voxel columns). The resampling process utilizes medial axes to ensure that voxel columns of appropriate lengths are used to capture the sought object surfaces. Then a geometric graph is constructed whose edges connect voxels in the resampled voxel columns and enforce the smoothness constraint and separation constraint on the sought surfaces. Validation of our algorithm was performed on the segmentation of airway trees and lung vascular trees in human in-vivo CT scans. Cost functions with directional information are applied to distinguish the airway inner wall and outer wall. We succeed in extracting the outer airway wall and optimizing the location of the inner wall in all cases, while the vascular trees are optimized as well. Comparing with the pre-segmentation results, our approach captures the wall surfaces more accurately, especially across bifurcations. The statistical evaluation on a double wall phantom derived from in-vivo CT images yields highly accurate results of the wall thickness measurement on the whole tree (with mean unsigned error 0.16 ± 0.16mm).
Details
- Title: Subtitle
- Optimal graph search based image segmentation for objects with complex topologies
- Creators
- Xiaomin Liu - University of Notre DameDanny Z Chen - University of Notre DameXiaodong Wu - University of IowaMilan Sonka - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.7259(1), pp.725915-7259110
- Conference
- Medical Imaging 2009: Image Processing
- DOI
- 10.1117/12.811704
- ISSN
- 0277-786X
- Language
- English
- Date published
- 02/26/2009
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; The Iowa Institute for Biomedical Imaging; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186692102771
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