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A Hybrid 3DCNN and 3DC-LSTM Based Model for 4D Spatio-Temporal fMRI Data: An ABIDE Autism Classification Study

Autor: el-Gazzar, Ahmed, Quaak, Mirjam, Cerliani, Leonardo, Bloem, Peter, van Wingen, Guido, Mani Thomas, Rajat, Zhou, Luping, Sarikaya, Duygu, Kia, Seyed Mostafa, Speidel, Stefanie, Malpani, Anand, Hashimoto, Daniel, Habes, Mohamad, Löfstedt, Tommy, Ritter, Kerstin, Wang, Hongzhi

Publikováno v: OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging ISBN: 9783030326944
OR/MLCN@MICCAI
OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging-2nd International Workshop, OR 2.0 2019, and 2nd International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Proceedings, 11796 LNCS, 95-102

Functional Magnetic Resonance Imaging (fMRI) captures the temporal dynamics of neural activity as a function of spatial location in the brain. Thus, fMRI scans are represented as 4-Dimensional (3-space + 1-time) tensors. And it is widely believed tha

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::881d1fead3a3fea5408a916dfcd7d81c
https://doi.org/10.1007/978-3-030-32695-1_11