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https://accedacris.ulpgc.es/jspui/handle/10553/154913
| Título: | On the Implementation of Planar 3D Transfer Learning for End to End Unimodal MRI Unbalanced Data Segmentation | Autores/as: | Kolarik, Martin Burget, Radim Travieso-González, Carlos M. Kocica, Jan |
Clasificación UNESCO: | 33 Ciencias tecnológicas | Palabras clave: | Multiple Sclerosis Reproducibility Segmentation Transfer Learning |
Fecha de publicación: | 2021 | Editor/a: | Springer | Publicación seriada: | Third International Workshop Reproducible Research In Pattern Recognition, Rrpr 2021 | Resumen: | 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. | URI: | https://accedacris.ulpgc.es/jspui/handle/10553/154913 | ISBN: | 978-3-030-76423-4 | DOI: | 10.1007/978-3-030-76423-4_10 | Fuente: | Third International Workshop Reproducible Research In Pattern Recognition, RRPR 2021 |
| Colección: | Actas de congresos |
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