Journal article
Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis
Medical physics (Lancaster), Vol.35(8), pp.3637-3649
07/17/2008
DOI: 10.1118/1.2953567
PMCID: PMC2809710
PMID: 18777924
Abstract
There are several medical application areas that require the segmentation and separation of the component bones of joints in a sequence of images of the joint acquired under various loading conditions, our own target area being joint motion analysis. This is a challenging problem due to the proximity of bones at the joint, partial volume effects, and other imaging modality-specific factors that confound boundary contrast. In this article, a two-step model-based segmentation strategy is proposed that utilizes the unique context of the current application wherein the shape of each individual bone is preserved in all scans of a particular joint while the spatial arrangement of the bones alters significantly among bones and scans. In the first step, a rigid deterministic model of the bone is generated from a segmentation of the bone in the image corresponding to one position of the joint by using the live wire method. Subsequently, in other images of the same joint, this model is used to search for the same bone by minimizing an energy function that utilizes both boundary- and region-based information. An evaluation of the method by utilizing a total of 60 data sets on MR and CT images of the ankle complex and cervical spine indicates that the segmentations agree very closely with the live wire segmentations, yielding true positive and false positive volume fractions in the range 89%-97% and 0.2%-0.7%. The method requires
1
-
2
minutes
of operator time and
6
-
7
min
of computer time per data set, which makes it significantly more efficient than live wire-the method currently available for the task that can be used routinely.
Details
- Title: Subtitle
- Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis
- Creators
- Jiamin Liu - Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021Jayaram Udupa - Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021Punam Saha - Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021Dewey Odhner - Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021Bruce Hirsch - Department of Neurobiology and Anatomy, Drexel University, College of Medicine, and Medical Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021Sorin Siegler - Department of Mechanical Engineering, Drexel University, Philadelphia, Pennsylvania 19104Scott Simon - Department of Neurosurgery, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021Beth Winkelstein - Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6021
- Resource Type
- Journal article
- Publication Details
- Medical physics (Lancaster), Vol.35(8), pp.3637-3649
- DOI
- 10.1118/1.2953567
- PMID
- 18777924
- PMCID
- PMC2809710
- NLM abbreviation
- Med Phys
- ISSN
- 0094-2405
- eISSN
- 2473-4209
- Publisher
- American Association of Physicists in Medicine
- Language
- English
- Date published
- 07/17/2008
- Academic Unit
- Radiology; Electrical and Computer Engineering
- Record Identifier
- 9984051703102771
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