Autoencoders for Multi-Label Prostate MR Segmentation
Image and Video Processing
2018-06-27 v2 Neural and Evolutionary Computing
Abstract
Organ image segmentation can be improved by implementing prior knowledge about the anatomy. One way of doing this is by training an autoencoder to learn a lowdimensional representation of the segmentation. In this paper, this is applied in multi-label prostate MR segmentation, with some positive results.
Keywords
Cite
@article{arxiv.1806.08216,
title = {Autoencoders for Multi-Label Prostate MR Segmentation},
author = {Ard de Gelder and Henkjan Huisman},
journal= {arXiv preprint arXiv:1806.08216},
year = {2018}
}
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