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Full article: https://www.ajronline.org/doi/10.2214/ajr.23.29570
Childhood obesity is a growing epidemic globally. Precisely quantifying abdominal fat distribution on MRI could be valuable for research and clinical care, but manual segmentation is extremely tedious. Farzaneh Ghazi Sherbaf, MD discusses a recent study in which the authors developed and validated an AI method to automatically segment subcutaneous and visceral abdominal fat on MRI in adolescents. The work has implications for making obesity research and care more effective through automated, personalized abdominal fat mapping.
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Full article: https://www.ajronline.org/doi/10.2214/ajr.23.29570
Childhood obesity is a growing epidemic globally. Precisely quantifying abdominal fat distribution on MRI could be valuable for research and clinical care, but manual segmentation is extremely tedious. Farzaneh Ghazi Sherbaf, MD discusses a recent study in which the authors developed and validated an AI method to automatically segment subcutaneous and visceral abdominal fat on MRI in adolescents. The work has implications for making obesity research and care more effective through automated, personalized abdominal fat mapping.
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