Novel segmentation method for abdominal fat quantification by MRI

Journal of Magnetic Resonance Imaging

Volumn 34, Issue 4, 2011, Pages 852-860

  Zhou, Anqi ^a   Murillo, Horacio ^a   Peng, Qi ^a,b  

^a UNIVERSITY OF TEXAS HEALTH SCIENCE CENTER AT SAN ANTONIO   (United States)

^b ALBERT EINSTEIN COLLEGE OF MEDICINE   (United States)

Author keywords

abdominal MRI; body composition; obesity; partial volume effect; visceral adipose tissue

Indexed keywords

ABDOMINAL FAT; ABDOMINAL SUBCUTANEOUS FAT; ADULT; ARTICLE; BODY FAT DISTRIBUTION; FEASIBILITY STUDY; FEMALE; HISTOGRAM; HUMAN; HUMAN EXPERIMENT; INTRAABDOMINAL FAT; MALE; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; SIGNAL NOISE RATIO;

ABDOMINAL FAT; ADIPOSE TISSUE; ANALYSIS OF VARIANCE; BODY COMPOSITION; FEASIBILITY STUDIES; FUZZY LOGIC; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; OBESITY; REPRODUCIBILITY OF RESULTS; SAMPLING STUDIES; WATER;

EID: 80052980661     PISSN: 10531807     EISSN: 15222586     Source Type: Journal    
DOI: 10.1002/jmri.22673     Document Type: Article

References (24)

1. Visscher TL, Seidell JC,. The public health impact of obesity. Ann Rev Public Health 2001; 22: 355-375. (Pubitemid 32452512)
2. Despres JP, Lemieux I,. Abdominal obesity and metabolic syndrome. Nature 2006; 444: 881-887. (Pubitemid 46024995)
3. Kopelman PG,. Obesity as a medical problem. Nature 2000; 404: 635-643. (Pubitemid 30205068)
4. Ibrahim MM,. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev 2010; 11: 11-18.
5. Fuller MF, Fowler PA, McNeill G, Foster MA,. Imaging techniques for the assessment of body composition. J Nutr 1994; 124 (Suppl): 1546S-1550S. (Pubitemid 24283434)
6. van der Kooy K, Seidell JC,. Techniques for the measurement of visceral fat: a practical guide. Int J Obes Relat Metab Disord 1993; 17: 187-196. (Pubitemid 23133348)
7. Gonzalez Ballester M, Zisserman AP, Brady M,. Estimation of the partial volume effect in MRI. Med Image Anal 2002; 6: 389-405. (Pubitemid 35363947)
8. Peng Q, Zhou A, Ding Y, McColl RW, Weatherall PT,. Visceral fat quantification on MRI: the impact of partial volume effect. In: Proceedings of the 16th Annual Meeting of ISMRM, Toronto, Canada. (abstract 3042).
9. Staten MA, Totty WG, Kohrt WM,. Measurement of fat distribution by magnetic resonance imaging. Invest Radiol 1989; 24: 345-349. (Pubitemid 19168428)
10. Machann J, Thamer C, Schnoedt B, et al. Standardized assessment of whole body adipose tissue topography by MRI. J Magn Reson Imaging 2005; 21: 455-462. (Pubitemid 40446442)
11. Lancaster JL, Ghiatas AA, Alyassin A, Kilcoyne RF, Bonora E, DeFronzo RA,. Measurement of abdominal fat with T1-weighted MR images. J Magn Reson Imaging 1991; 1: 363-369.
12. Peng Q, McColl RW, Wang JH, Chia JM, Weatherall PT,. Water-saturated three-dimensional balanced steady-state free precession for fast abdominal fat quantification. J Magn Reson Imaging 2005; 21: 263-271. (Pubitemid 40280121)
13. Armao D, Guyon JP, Firat Z, Brown MA, Semelka RC,. Accurate quantification of visceral adipose tissue (VAT) using water-saturation MRI and computer segmentation: preliminary results. J Magn Reson Imaging 2006; 23: 736-741.
14. Peng Q, McColl RW, Ding Y, Wang J, Chia JM, Weatherall PT,. Automated method for accurate abdominal fat quantification on water-saturated magnetic resonance images. J Magn Reson Imaging 2007; 26: 738-746. (Pubitemid 350194600)
15. Reeder SB, McKenzie CA, Pineda AR, et al. Water-fat separation with IDEAL gradient-echo imaging. J Magn Reson Imaging 2007; 25: 644-652. (Pubitemid 46355429)
16. Chuang KS, Tzeng HL, Chen S, Wu J, Chen TJ,. Fuzzy c-means clustering with spatial information for image segmentation. Comput Med Imaging Graph 2006; 30: 9-15. (Pubitemid 43162367)
17. Banerjee S, Mukherjee DP, Majumdar DD,. Fuzzy c-means approach to tissue classification in multimodal medical imaging. Inform Sciences 1999; 115: 261-279.
18. Likar B, Maintz JB, Viergever MA, Pernus F,. Retrospective shading correction based on entropy minimization. J Microsc 2000; 197 (Pt 3): 285-295. (Pubitemid 30143808)
19. Belaroussi B, Milles J, Carme S, Zhu YM, Benoit-Cattin H,. Intensity non-uniformity correction in MRI: existing methods and their validation. Med Image Anal 2006; 10: 234-246. (Pubitemid 43174976)
20. Baruch O, Loew MH,. Segmentation of two-dimensional boundaries using the chain code. Pattern Recognit 1988; 21: 581-589.
21. Liu KH, Chan YL, Chan WB, Kong WL, Kong MO, Chan JC,. Sonographic measurement of mesenteric fat thickness is a good correlate with cardiovascular risk factors: comparison with subcutaneous and preperitoneal fat thickness, magnetic resonance imaging and anthropometric indexes. Int J Obes Relat Metab Disord 2003; 27: 1267-1273. (Pubitemid 37281676)
22. Liou TH, Chan WP, Pan LC, Lin PW, Chou P, Chen CH,. Fully automated large-scale assessment of visceral and subcutaneous abdominal adipose tissue by magnetic resonance imaging. Int J Obes (Lond) 2006; 30: 844-852.
23. Demerath EW, Ritter KJ, Couch WA, et al. Validity of a new automated software program for visceral adipose tissue estimation. Int J Obes (Lond) 2007; 31: 285-291. (Pubitemid 46183135)
24. Positano V, Gastaidelli A, Sironi AM, Santarelli MF, Lombardi M, Landini L,. An accurate and robust method for unsupervised assessment of abdominal fat by MRI. J Magn Reson Imaging 2004; 20: 684-689. (Pubitemid 39313745)