@inproceedings{e80e8c70bd1d4276bb18094383b530b6,
title = "Over-and-Under Complete Convolutional RNN for MRI Reconstruction",
abstract = "Reconstructing magnetic resonance (MR) images from under-sampled data is a challenging problem due to various artifacts introduced by the under-sampling operation. Recent deep learning-based methods for MR image reconstruction usually leverage a generic auto-encoder architecture which captures low-level features at the initial layers and high-level features at the deeper layers. Such networks focus much on global features which may not be optimal to reconstruct the fully-sampled image. In this paper, we propose an Over-and-Under Complete Convolutional Recurrent Neural Network (OUCR), which consists of an overcomplete and an undercomplete Convolutional Recurrent Neural Network (CRNN). The overcomplete branch gives special attention in learning local structures by restraining the receptive field of the network. Combining it with the undercomplete branch leads to a network which focuses more on low-level features without losing out on the global structures. Extensive experiments on two datasets demonstrate that the proposed method achieves significant improvements over the compressed sensing and popular deep learning-based methods with less number of trainable parameters.",
keywords = "Convolutional RNN, Deep learning, MRI reconstruction",
author = "Pengfei Guo and Valanarasu, {Jeya Maria Jose} and Puyang Wang and Jinyuan Zhou and Shanshan Jiang and Patel, {Vishal M.}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 ; Conference date: 27-09-2021 Through 01-10-2021",
year = "2021",
doi = "10.1007/978-3-030-87231-1_2",
language = "English (US)",
isbn = "9783030872304",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "13--23",
editor = "{de Bruijne}, Marleen and {de Bruijne}, Marleen and Cattin, {Philippe C.} and St{\'e}phane Cotin and Nicolas Padoy and Stefanie Speidel and Yefeng Zheng and Caroline Essert",
booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 - 24th International Conference, Proceedings",
address = "Germany",
}