Vytisknout
0563909 - ÚPT 2023 RIV US eng J - Článek v odborném periodiku
Shamaei, Amirmohammad - Starčuková, Jana - Pavlova, Iveta - Starčuk jr., Zenon
Model-informed unsupervised deep learning approaches to frequency and phase correction of MRS signals.
Magnetic Resonance in Medicine. Roč. 89, č. 3 (2023), s. 1221-1236. ISSN 0740-3194. E-ISSN 1522-2594
GRANT EU: European Commission(XE) 813120 - INSPiRE-MED
Institucionální podpora: RVO:68081731
Klíčová slova: deep learning * edited MRS * frequency correction * MR spectroscopy * phase correction
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 3.3, rok: 2022
Způsob publikování: Open access
https://onlinelibrary.wiley.com/doi/10.1002/mrm.29498
Trvalý link: https://hdl.handle.net/11104/0335691
Shamaei, Amirmohammad - Starčuková, Jana - Pavlova, Iveta - Starčuk jr., Zenon
Model-informed unsupervised deep learning approaches to frequency and phase correction of MRS signals.
Magnetic Resonance in Medicine. Roč. 89, č. 3 (2023), s. 1221-1236. ISSN 0740-3194. E-ISSN 1522-2594
GRANT EU: European Commission(XE) 813120 - INSPiRE-MED
Institucionální podpora: RVO:68081731
Klíčová slova: deep learning * edited MRS * frequency correction * MR spectroscopy * phase correction
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 3.3, rok: 2022
Způsob publikování: Open access
https://onlinelibrary.wiley.com/doi/10.1002/mrm.29498
Trvalý link: https://hdl.handle.net/11104/0335691