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Journal article
Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis
Medical physics (Lancaster), v 35(8), pp 3637-3649
01 Aug 2008
PMID: 18777924
Featured in Collection : UN Sustainable Development Goals @ Drexel
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. (c) 2008 American Association of Physicists in Medicine.
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Details
- Title
- Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis
- Creators
- Jiamin Liu - University of PennsylvaniaJayaram K. Udupa - University of PennsylvaniaPunam K. Saha - University of PennsylvaniaDewey Odhner - University of PennsylvaniaBruce E. Hirsch - Drexel UniversitySorin Siegler - Drexel UniversityScott Simon - University of PennsylvaniaBeth A. Winkelstein - University of Pennsylvania
- Publication Details
- Medical physics (Lancaster), v 35(8), pp 3637-3649
- Publisher
- Wiley
- Number of pages
- 13
- Grant note
- R01AR046902 / NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Arthritis & Musculoskeletal & Skin Diseases (NIAMS) R01 EB004395; EB004395 / NIBIB NIH HHS; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Biomedical Imaging & Bioengineering (NIBIB) R01NS037172 / NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Neurological Disorders & Stroke (NINDS) R01 AR046902; AR46902 / NIAMS NIH HHS; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Arthritis & Musculoskeletal & Skin Diseases (NIAMS) NS37172; R01 NS037172 / NINDS NIH HHS; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Neurological Disorders & Stroke (NINDS) R01EB004395 / NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Biomedical Imaging & Bioengineering (NIBIB)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]; Mechanical Engineering and Mechanics
- Web of Science ID
- WOS:000258038900025
- Scopus ID
- 2-s2.0-48349105295
- Other Identifier
- 991019168688004721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Radiology, Nuclear Medicine & Medical Imaging