Document Detail


Topography mapping of whole body adipose tissue using A fully automated and standardized procedure.
MedLine Citation:
PMID:  20099357     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
PURPOSE: To obtain quantitative measures of human body fat compartments from whole body MR datasets for the risk estimation in subjects prone to metabolic diseases without the need of any user interaction or expert knowledge. MATERIALS AND METHODS: Sets of axial T1-weighted spin-echo images of the whole body were acquired. The images were segmented using a modified fuzzy c-means algorithm. A separation of the body into anatomic regions along the body axis was performed to define regions with visceral adipose tissue present, and to standardize the results. In abdominal image slices, the adipose tissue compartments were divided into subcutaneous and visceral compartments using an extended snake algorithm. The slice-wise areas of different tissues were plotted along the slice position to obtain topographic fat tissue distributions. RESULTS: Results from automatic segmentation were compared with manual segmentation. Relatively low mean deviations were obtained for the class of total tissue (4.48%) and visceral adipose tissue (3.26%). The deviation of total adipose tissue was slightly higher (8.71%). CONCLUSION: The proposed algorithm enables the reliable and completely automatic creation of adipose tissue distribution profiles of the whole body from multislice MR datasets, reducing whole examination and analysis time to less than half an hour.
Authors:
Christian W?rslin; J?rgen Machann; Hansj?rg Rempp; Claus Claussen; Bin Yang; Fritz Schick
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of magnetic resonance imaging : JMRI     Volume:  31     ISSN:  1522-2586     ISO Abbreviation:  J Magn Reson Imaging     Publication Date:  2010 Feb 
Date Detail:
Created Date:  2010-01-29     Completed Date:  2010-04-15     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9105850     Medline TA:  J Magn Reson Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  430-9     Citation Subset:  IM    
Affiliation:
Department of Diagnostic and Interventional Radiology, University of T?bingen, T?bingen, Germany. christian.wuerslin@med.uni-tuebingen.de
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MeSH Terms
Descriptor/Qualifier:
Adipose Tissue / anatomy & histology*
Algorithms
Artificial Intelligence
Body Fat Distribution / methods*,  standards
Germany
Humans
Image Enhancement / methods,  standards
Image Interpretation, Computer-Assisted / methods*,  standards
Imaging, Three-Dimensional / methods*,  standards
Magnetic Resonance Imaging / methods*,  standards
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Whole Body Imaging / methods*,  standards

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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