Literature DB >> 17282946

Performance Evaluation of Abdominal Fat Burden Quantification in CT.

Alok Bandekar1, Morteza Naghavi, Ioannis Kakadiaris.   

Abstract

Abdominal fat accumulation is an important cardiovascular risk ovascular risk factor. In clinical practice, delineation of subcutaneous and visceral fat is performed manually by an expert. This procedure is labor intensive, time consuming, and subject to inter-and intra-observer variability. In this paper, we present an extension of our previous work on automatic fat burden quantification and classification. Our improved method automatically differentiates abdominal fat into subcutaneous and visceral fat components and removes equipment-related artifacts. We evaluated the performance of our method using data from 40 subjects with very encouraging results.

Year:  2005        PMID: 17282946     DOI: 10.1109/IEMBS.2005.1617177

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  6 in total

1.  Computer-aided assessment of regional abdominal fat with food residue removal in CT.

Authors:  Sokratis Makrogiannis; Giorgio Caturegli; Christos Davatzikos; Luigi Ferrucci
Journal:  Acad Radiol       Date:  2013-11       Impact factor: 3.173

2.  Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: application to a longitudinal adult screening cohort.

Authors:  Scott J Lee; Jiamin Liu; Jianhua Yao; Andrew Kanarek; Ronald M Summers; Perry J Pickhardt
Journal:  Br J Radiol       Date:  2018-03-28       Impact factor: 3.039

3.  Automated separation of visceral and subcutaneous adiposity in in vivo microcomputed tomographies of mice.

Authors:  Svetlana Lublinsky; Yen K Luu; Clinton T Rubin; Stefan Judex
Journal:  J Digit Imaging       Date:  2008-09-03       Impact factor: 4.056

Review 4.  Quantification of adiposity in small rodents using micro-CT.

Authors:  S Judex; Y K Luu; E Ozcivici; B Adler; S Lublinsky; C T Rubin
Journal:  Methods       Date:  2009-06-10       Impact factor: 3.608

5.  Body fat assessment method using CT images with separation mask algorithm.

Authors:  Young Jae Kim; Seung Hyun Lee; Tae Yun Kim; Jeong Yun Park; Seung Hong Choi; Kwang Gi Kim
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

6.  Computerized Automated Quantification of Subcutaneous and Visceral Adipose Tissue From Computed Tomography Scans: Development and Validation Study.

Authors:  Young Jae Kim; Ji Won Park; Jong Wan Kim; Chan-Soo Park; John Paul S Gonzalez; Seung Hyun Lee; Kwang Gi Kim; Jae Hwan Oh
Journal:  JMIR Med Inform       Date:  2016-02-04
  6 in total

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