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Abstract #4110

Automated image segmentation of prostate MR elastography by dense-like U-net.

Nader Aldoj1, Federico Biavati1, Sebastian Stober2, Marc Dewey1, Patrick Asbach1, and Ingolf Sack1
1Charité, Berlin, Germany, 2Ovgu Magdeburg, Magdeburg, Germany

The purpose was to investigate the impact of individual or combined MR Elastogrphy maps and MRI sequences on the overall segmentation of prostate gland and its subsequent zones using dense-like U-net. Our study showed that the obtained dice score of MRE maps was higher (i.e. more accurate segmentation) than the one obtained with MRI sequences. Moreover, we found that the magnitude MRE map had the highest importance for accurate segmentation among all tested maps/sequences. In conclusion, MRE maps resulted in excellent segmentations even when compared to T2w images which are the standard choice for segmentation tasks.

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