Novel segmentation method for abdominal fat quantification by MRI

Anqi Zhou, Horacio Murillo, Qi Peng

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Purpose: To introduce and describe the feasibility of a novel method for abdominal fat segmentation on both water-saturated and non-water-saturated MR images with improved absolute fat tissue quantification. Materials and Methods: A general fat distribution model which fits both water-saturated (WS) and non-water-saturated (NWS) MR images based on image gray-level histogram is first proposed. Next, a novel fuzzy c-means clustering step followed by a simple thresholding is proposed to achieve automated and accurate abdominal quantification taking into consideration the partial-volume effects (PVE) in abdominal MR images. Eleven subjects were scanned at central abdomen levels with both WS and NWS MRI techniques. Synthesized "noisy" NWS (nNWS) images were also generated to study the impact of reduced SNR on fat quantification using the novel approach. The visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) amounts of the WS MR images were quantified with a traditional intensity thresholding method as a reference to evaluate the performance of the novel method on WS, NWS, and nNWS MR images. Results: The novel approach resulted in consistent SAT and VAT amounts for WS, NWS, and nNWS images. Automatic segmentation and incorporation of spatial information during segmentation improved speed and accuracy. These results were in good agreement with those from the WS images quantified with a traditional intensity thresholding method and accounted for PVE contributions. Conclusion: The proposed method using a novel fuzzy c-means clustering method followed by thresholding can achieve consistent quantitative results on both WS and NWS abdominal MR images while accounting for PVE contributing inaccuracies.

Original languageEnglish (US)
Pages (from-to)852-860
Number of pages9
JournalJournal of Magnetic Resonance Imaging
Volume34
Issue number4
DOIs
StatePublished - Oct 2011

Fingerprint

Abdominal Fat
Water
Intra-Abdominal Fat
Subcutaneous Fat
Fats
Cluster Analysis
Abdomen

Keywords

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

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Novel segmentation method for abdominal fat quantification by MRI. / Zhou, Anqi; Murillo, Horacio; Peng, Qi.

In: Journal of Magnetic Resonance Imaging, Vol. 34, No. 4, 10.2011, p. 852-860.

Research output: Contribution to journalArticle

Zhou, Anqi ; Murillo, Horacio ; Peng, Qi. / Novel segmentation method for abdominal fat quantification by MRI. In: Journal of Magnetic Resonance Imaging. 2011 ; Vol. 34, No. 4. pp. 852-860.
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