Košík

0570880 - ÚPT 2024 RIV GB eng J - Článek v odborném periodiku
Shamaei, Amirmohammad - Starčuková, Jana - Starčuk jr., Zenon
Physics-informed deep learning approach to quantification of human brain metabolites from magnetic resonance spectroscopy data.
Computers in Biology Medicine. Roč. 158, May (2023), č. článku 106837. ISSN 0010-4825. E-ISSN 1879-0534
Grant CEP: GA MŠMT(CZ) EF18_046/0016045; GA MŠMT(CZ) LM2018129; GA MŠMT(CZ) LM2023050
GRANT EU: European Commission(XE) 813120 - INSPiRE-MED
Institucionální podpora: RVO:68081731
Klíčová slova: MR spectroscopy * Inverse problem * Deep learning * Machine learning * Convolutional neural network * Metabolite quantification
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impakt faktor: 7.7, rok: 2022
Způsob publikování: Open access
https://www.sciencedirect.com/science/article/pii/S0010482523003025
Trvalý link: https://hdl.handle.net/11104/0342210