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Field Map Estimation for Effective Fat Quantification at High Field MRI

고자장 자기공명영상에서 효율적인 지방 정량화를 위한 필드 맵 측정 기술

  • 은성종 (가천대학교 전자계산학과) ;
  • 황보택근 (가천대학교 IT대학 인터랙티브미디어학과)
  • Received : 2014.10.07
  • Accepted : 2014.11.18
  • Published : 2014.11.28

Abstract

The number of fatty liver patients is sharply growing due to the rapid increase in the incidence of metabolic syndrome, which can lead to diseases such as abdominal obesity, hypertension, diabetes, and hyperlipidemia. Early diagnosis requires examinations using magnetic resonance imaging (MRI), wherein quantitative analyses are implemented through a professional water-fat separation method in many cases, as the intensity values of the areas of interest and non-interest are considerably similar or the same. However, such separation method generates inaccurate results in high magnetic fields, where the inhomogeneity of the fields increases. To overcome the limits of such conventional fat quantification methods, this paper proposes a field map estimation method that is effective in high magnetic fields. This method generates field maps through echo images that are obtained using the existing IDEAL sequences, and considers the wrapping degree of the field maps. Then clustering is performed to separate calibration areas, the least square fits based on the region growing method schema of the separated calibration areas, and the histograms are adjusted to separate the water from the fats. In experiment results, our proposed method had a superior fat detection rate of an average of 86.4%, compared to the ideal method with an average of 61.5% and Yu's method with an average of 62.6%. In addition, it was confirmed that the proposed method had a more accurate water detection rate of 98.4% on the average than the 88.6% average of the fat saturation method.

Keywords

MRI;Water-fat Separation;Field Map Estimation;High-field MR;Region Growing Scheme

Acknowledgement

Supported by : 가천대학교

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