Publication detail

On the Implementation of Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation

KOLAŘÍK, M. BURGET, R. TRAVIESO-GONZÁLEZ, C. KOČICA, J.

Original Title

On the Implementation of Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation

Type

conference paper

Language

English

Original Abstract

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.

Keywords

Multiple sclerosis; Reproducibility; Segmentation; transfer learning

Authors

KOLAŘÍK, M.; BURGET, R.; TRAVIESO-GONZÁLEZ, C.; KOČICA, J.

Released

14. 5. 2021

Publisher

Springer, Cham

Location

Online

ISBN

978-3-030-76422-7

Book

Reproducible Research in Pattern Recognition

Edition

Third International Workshop, RRPR 2021, Virtual Event, January 11, 2021, Revised Selected Papers

Pages from

146

Pages to

151

Pages count

7

URL

https://link.springer.com/chapter/10.1007/978-3-030-76423-4_10

BibTex

@inproceedings{BUT172287,
  author="KOLAŘÍK, M. and BURGET, R. and TRAVIESO-GONZÁLEZ, C. and KOČICA, J.",
  title="On the Implementation of Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation",
  booktitle="Reproducible Research in Pattern Recognition",
  year="2021",
  series="Third International Workshop, RRPR 2021, Virtual Event, January 11, 2021, Revised Selected Papers",
  pages="146--151",
  publisher="Springer, Cham",
  address="Online",
  doi="10.1007/978-3-030-76423-4\{_}10",
  isbn="978-3-030-76422-7",
  url="https://link.springer.com/chapter/10.1007/978-3-030-76423-4_10"
}