The last decades have seen an increasing socioeconomic impact of obesity and obesity-related diseases. Noninvasive measures like subcutaneous and visceral adipose tissue (SAT, VAT) amounts and are also increasingly correlated with other, often clinical or metabolic findings as well as independent patient characteristics, even interventional complication rates. MRI fat quantification is common but manual processing is often laborious and time consuming while fully automatic segmentation is prone to errors. This work takes a custom-made semiautomatic MRI tool and prospectively analyzes the processing and interaction times for readers with different experience as well as patients from different BMI groups.
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