Abdominal fat quantification using convolutional networks.

Objectives: To present software for automated adipose tissue quantification of abdominal magnetic resonance imaging (MRI) data using fully convolutional networks (FCN) and to evaluate its overall performance-accuracy, reliability, processing effort, and time-in comparison with an interactive reference method.

Materials And Methods: Single-center data of patients with obesity were analyzed retrospectively with institutional review board approval. Ground truth for subcutaneous (SAT) and visceral adipose tissue (VAT) segmentation was provided by semiautomated region-of-interest (ROI) histogram thresholding of 331 full abdominal image series.

Anthropometric estimators of abdominal fat volume in adults with overweight and obesity.

Background/objectives: To evaluate anthropometric measures for the prediction of whole-abdominal adipose tissue volumes V (subcutaneous V, visceral V and total V) in patients with obesity.

Subjects/methods: A total of 181 patients (108 women) with overweight or obesity were analyzed retrospectively. MRI data (1.

Abdominal subcutaneous fat quantification in obese patients from limited field-of-view MRI data.

Different types of adipose tissue can be accurately localized and quantified by tomographic imaging techniques (MRI or CT). One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities.

Estimation of abdominal subcutaneous fat volume of obese adults from single-slice MRI data - Regression coefficients and agreement.

Purpose: Cross-sectional imaging is increasingly used to quantify adipose tissue compartments in subjects with overweight or obesity. The lack of ionizing radiation makes magnetic resonance imaging (MRI) highly preferable to computed tomography (CT) although it is generally less standardized and time-consuming. Fat areas of single or stacks of neighboring slices have previously been considered as surrogates to avoid laborious processing of whole abdominal data-but studies are inconsistent in design and results.

Half-body MRI volumetry of abdominal adipose tissue in patients with obesity.

Background: The purpose of this study was to determine to what extent the whole volumes of abdominal subcutaneous (ASAT) and visceral adipose tissue (VAT) of patients with obesity can be predicted by using data of one body half only. Such a workaround has already been reported for dual-energy x-ray absorption (DEXA) scans and becomes feasible whenever the field of view of an imaging technique is not large enough.

Methods: Full-body abdominal MRI data of 26 patients from an obesity treatment center (13 females and 13 males, BMI range 30.