@inproceedings{86a6d3050b964bf2a80f840d70f3614a,
title = "Multi-scale networks for segmentation of brain magnetic resonance images",
abstract = "Measuring the distribution of major brain tissues using magnetic resonance (MR) images has attracted extensive research efforts. Due to its remarkable success, deep learning-based image segmentation has been applied to this problem, in which the size of patches usually represents a tradeoff between complexity and accuracy. In this paper, we propose the multi-size-and-position neural network (MSPNN) for brain MR image segmentation. Our contributions include (1) jointly using U-Nets trained on large patches and back propagation neural networks (BPNNs) trained on small patches for segmentation, and (2) adopting the convolutional auto-encoder (CAE) to restore MR images before applying them to BPNNs. We have evaluated this algorithm against five widely used brain MR image segmentation approaches on both synthetic and real MR studies. Our results indicate that the proposed algorithm can segment brain MR images effectively and provide precise distribution of major brain tissues.",
keywords = "Back propagation neural network (BPNN), Brain MR image segmentation, Convolutional auto-encoder (CAE), Deep learning, U-Net",
author = "Jie Wei and Yong Xia",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 3rd International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017 and 7th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 ; Conference date: 14-09-2017 Through 14-09-2017",
year = "2017",
doi = "10.1007/978-3-319-67558-9_36",
language = "英语",
isbn = "9783319675572",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "312--320",
editor = "Tal Arbel and Cardoso, {M. Jorge}",
booktitle = "Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - 3rd International Workshop, DLMIA 2017 and 7th International Workshop, ML-CDS 2017 Held in Conjunction with MICCAI 2017, Proceedings",
}