Abstract #3486

Automated segmentation of abdominal organs in T1-weighted MR images using a deep learning approach: application on a large epidemiological MR study

Thomas Küstner^1,2, Marc Fischer¹, Sarah Müller², Daniel Guttmann¹, Konstantin Nikolaou¹, Fabian Bamberg¹, Bin Yang², Fritz Schick¹, and Sergios Gatidis¹

¹University of Tübingen, Tübingen, Germany, ²University of Stuttgart, Stuttgart, Germany

In this study we implemented and validated an automated method for segmentation of T1-weighted MR images using a deep learning approach. We applied the algorithm two 80 training and 20 validation data sets drawn from an epidemiological MR study and observed high accuracy compared to manual tumor segmentation. This approach can potentially contribute to efficient analysis of large epidemiological MR studies in the future.

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