On the Implementation of Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation
Martin Kolarik  1  , Radim Burget  1  , Carlos M. Travieso-Gonzalez  2  , Jan Kocica  3  
1 : Brno University of Technology [Brno]  (BUT)  -  Website
Antonínská 548/1601 90 BrnoCzech Republic -  Czech Republic
2 : University of Las Palmas de Gran Canaria  (ULPGC)  -  Website
Calle Juan de Quesada, 35001 Las Palmas de Gran Canaria, Las Palmas -  Spain
3 : Masaryk University and University Hospital Brno

This article describes detailed notes on the practical implementation of our paper Planar 3D transfer learning for end to end unimodal MRI unbalanced data segmentation (ICPR 2020, Milan), which deals with a problem of multiple sclerosis lesion segmentation from a unimodal MRI flair brain scan by applying a planar 3D transfer learning backbone weights to an autoencoder segmentation neural network. Our source code is published online under an open-source license, and we provide step-by-step instructions for the reproduction of our results.



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