| Computer-aided assessment of anomalies in the scoliotic spine in 3-D MRI images. | |
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MedLine Citation:
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PMID: 20426187 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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The assessment of anomalies in the scoliotic spine using Magnetic Resonance Imaging (MRI) is an essential task during the planning phase of a patient's treatment and operations. Due to the pathologic bending of the spine, this is an extremely time consuming process as an orthogonal view onto every vertebra is required. In this article we present a system for computer-aided assessment (CAA) of anomalies in 3-D MRI images of the spine relying on curved planar reformations (CPR). We introduce all necessary steps, from the pre-processing of the data to the visualization component. As the core part of the framework is based on a segmentation of the spinal cord we focus on this. The proposed segmentation method is an iterative process. In every iteration the segmentation is updated by an energy based scheme derived from Markov random field (MRF) theory. We evaluate the segmentation results on public available clinical relevant 3-D MRI data sets of scoliosis patients. In order to assess the quality of the segmentation we use the angle between automatically computed planes through the vertebra and planes estimated by medical experts. This results in a mean angle difference of less than six degrees. |
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Authors:
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Florian J?ger; Joachim Hornegger; Siegfried Schwab; Rolf Janka |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Volume: 12 ISSN: - ISO Abbreviation: Med Image Comput Comput Assist Interv Publication Date: 2009 |
Date Detail:
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Created Date: 2010-04-29 Completed Date: 2010-06-07 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101249582 Medline TA: Med Image Comput Comput Assist Interv Country: Germany |
Other Details:
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Languages: eng Pagination: 819-26 Citation Subset: IM |
Affiliation:
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Department of Computer Science, University of Erlangen, Germany. jaeger@informatik.uni-erlangen.de |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Artificial Intelligence* Humans Image Enhancement / methods Image Interpretation, Computer-Assisted / methods* Magnetic Resonance Imaging / methods* Pattern Recognition, Automated / methods* Reproducibility of Results Scoliosis / pathology* Sensitivity and Specificity Spine / pathology* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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