@inproceedings{62b730ecae9b46acb0240a1a803f5244,
title = "Dictionary learning and sparse coding-based denoising for high-resolution task functional connectivity MRI analysis",
abstract = "We propose a novel denoising framework for task functional Magnetic Resonance Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the brain functional connectivity via dictionary learning and sparse coding (DLSC). In order to address the limitations of the unsupervised DLSC-based fMRI studies, we utilize the prior knowledge of task paradigm in the learning step to train a data-driven dictionary and to model the sparse representation. We apply the proposed DLSC-based method to Human Connectome Project (HCP) motor tfMRI dataset. Studies on the functional connectivity of cerebrocerebellar circuits in somatomotor networks show that the DLSC-based denoising framework can significantly improve the prominent connectivity patterns, in comparison to the temporal non-local means (tNLM)-based denoising method as well as the case without denoising, which is consistent and neuroscientifically meaningful within motor area. The promising results show that the proposed method can provide an important foundation for the high-resolution functional connectivity analysis, and provide a better approach for fMRI preprocessing.",
keywords = "Connectivity, Denoising, Dictionary learning, Functional magnetic resonance imaging (fMRI), Sparse coding",
author = "Seongah Jeong and Xiang Li and Jiarui Yang and Quanzheng Li and Vahid Tarokh",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017 held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 ; Conference date: 10-09-2017 Through 10-09-2017",
year = "2017",
doi = "10.1007/978-3-319-67389-9_6",
language = "English",
isbn = "9783319673882",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "45--52",
editor = "Yinghuan Shi and Heung-Il Suk and Kenji Suzuki and Qian Wang",
booktitle = "Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Proceedings",
address = "Germany",
}