RATIONALE AND OBJECTIVES: Develop a deep learning-based algorithm using the U-Net architecture to measure abdominal fat on computed tomography (CT) images.
Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, cardiovascular diseases, and cancer. Magnetic resonance imaging (MRI) is an accurate method for determination of body fat volume and distribution. How...
Computer methods and programs in biomedicine
Mar 21, 2017
Accurately assessment of adipose tissue volume inside a human body plays an important role in predicting disease or cancer risk, diagnosis and prognosis. In order to overcome limitation of using only one subjectively selected CT image slice to estima...
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
OBJECTIVE: The objective was to develop a fully automated algorithm for abdominal fat segmentation and to deploy this method at scale in an academic biobank.
Obesity is a low-grade chronic inflammatory state, in which a cytokine chemerin with its immunometabolic modulation has an important role. We aimed to study in a healthy population relationships between serum chemerin levels, lifestyle choices and ma...
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