Previous classification techniques for determining the quantification of white adipose tissue and brown adipose tissue have relied on using fat fraction and proton relaxation times using fixed peak spectroscopic models. Machine learning algorithms have proven to be highly accurate for image segmentation but their accuracies rely heavily on input datasets. By using the recently proposed Multi-Varying MR Spectroscopy model an increase in dataset specificity can be applied to each voxel by addition of varying fat peak intensity values. Using this new dataset, four machine learning models were compared.
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