@inproceedings{482688525cf34bcaaeefce9a3dd28e0e,
title = "Acceleration of High-Resolution 3D MR Fingerprinting via a Graph Convolutional Network",
abstract = "Magnetic resonance fingerprinting (MRF) is a novel imaging framework for fast and simultaneous quantification of multiple tissue properties. Recently, 3D MRF methods have been developed, but the acquisition speed needs to be improved before they can be adopted for clinical use. The purpose of this study is to develop a novel deep learning approach to accelerate 3D MRF acquisition along the slice-encoding direction in k-space. We introduce a graph-based convolutional neural network that caters to non-Cartesian spiral trajectories commonly used for MRF acquisition. We improve tissue quantification accuracy compared with the state of the art. Our method enables fast 3D MRF with high spatial resolution, allowing whole-brain coverage within 5 min, making MRF more feasible in clinical settings.",
keywords = "3D MR fingerprinting, GRAPPA, Graph convolution, K-space interpolation",
author = "Feng Cheng and Yong Chen and Xiaopeng Zong and Weili Lin and Dinggang Shen and Yap, {Pew Thian}",
note = "Funding Information: This work was supported in part by NIH grant EB022880. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 ; Conference date: 04-10-2020 Through 08-10-2020",
year = "2020",
doi = "10.1007/978-3-030-59713-9_16",
language = "English",
isbn = "9783030597122",
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 = "158--166",
editor = "Martel, {Anne L.} and Purang Abolmaesumi and Danail Stoyanov and Diana Mateus and Zuluaga, {Maria A.} and Zhou, {S. Kevin} and Daniel Racoceanu and Leo Joskowicz",
booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 - 23rd International Conference, Proceedings",
address = "Germany",
}