Keywords: Segmentation, Fat, brown adipose tissue
The noninvasive assessment of BAT volume is fundamental for characterizing the longitudinal effects in rodents. In this work, dynamic fat fraction images of 34 rats fed under different conditions were acquired before and after noradrenaline injection for 2.5 hours. The iBAT regions were recognized and labelled automatically by identifying the regions with significant changes in FF images. Then a deep learning network was built up by training the FF images and the automatically identified mask images in all rats. The dice similarity coefficient, precision rate and recall rate of the network were found to be 0.897±0.061, 0.901±0.068 and 0.889±0.086, respectively.
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