Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction.
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| Title: | Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction. |
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| Authors: | Schauman SS; Department of Radiology, Stanford University, Stanford, CA, USA. sophie.schauman.academic@gmail.com.; Department of Clinical Neuroscience, Karolinska Institute, Stockholm, 17177, Sweden. sophie.schauman.academic@gmail.com., Iyer SS; Department of Radiology, Stanford University, Stanford, CA, USA.; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA., Sandino CM; Department of Electrical Engineering, Stanford University, Stanford, CA, USA., Yurt M; Department of Electrical Engineering, Stanford University, Stanford, CA, USA., Cao X; Department of Radiology, Stanford University, Stanford, CA, USA., Liao C; Department of Radiology, Stanford University, Stanford, CA, USA., Ruengchaijatuporn N; Center of Excellence in Computational Molecular Biology, Chulalongkorn University, Bangkok, Thailand.; Center for Artificial Intelligence in Medicine, Chulalongkorn University, Bangkok, Thailand., Chatnuntawech I; National Nanotechnology Center, National Science and Technology Development Agency, Pathum Thani, Thailand., Tong E; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA., Setsompop K; Department of Radiology, Stanford University, Stanford, CA, USA.; Department of Electrical Engineering, Stanford University, Stanford, CA, USA. |
| Source: | Magma (New York, N.Y.) [MAGMA] 2025 Apr; Vol. 38 (2), pp. 221-237. Date of Electronic Publication: 2025 Feb 01. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: Germany NLM ID: 9310752 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1352-8661 (Electronic) Linking ISSN: 09685243 NLM ISO Abbreviation: MAGMA Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1352-8661 |
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| DOI: | 10.1007/s10334-024-01222-2 |
