Linked Life Data

18840956

Source:http://linkedlifedata.com/resource/pubmed/id/18840956

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
9
pubmed:dateCreated
2008-10-8
pubmed:abstractText
The objective of this study was to develop a computing tool for full-automatic segmentation of body fat distributions on volumetric CT images. We developed an algorithm to automatically identify the body perimeter and the inner contour that separates visceral fat from subcutaneous fat. Diaphragmatic surfaces can be extracted by model-based segmentation to match the bottom surface of the lung in CT images for determination of the upper limitation of the abdomen. The functions for quantitative evaluation of abdominal obesity or obesity-related metabolic syndrome were implemented with a prototype three-dimensional (3D) image processing workstation. The volumetric ratios of visceral fat to total fat and visceral fat to subcutaneous fat for each subject can be calculated. Additionally, color intensity mapping of subcutaneous areas and the visceral fat layer is quite obvious in understanding the risk of abdominal obesity with the 3D surface display. Preliminary results obtained have been useful in medical checkups and have contributed to improved efficiency in checking obesity throughout the whole range of the abdomen with 3D visualization and analysis.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0369-4305
pubmed:author
pubmed:issnType
Print
pubmed:day
20
pubmed:volume
64
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1177-81
pubmed:dateRevised
2011-7-28
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Development of an automated 3D segmentation program for volume quantification of body fat distribution using CT.
pubmed:affiliation
Fujifilm Medical Co., Ltd.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't