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- 1.0544182 - ÚPT 2022 RIV PT eng C - Conference Paper (international conference)
Shamaei, Amirmohammad - Starčuková, Jana - Starčuk jr., Zenon
A wavelet scattering convolutional network for magnetic resonance spectroscopy signal quantitation.
Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies. Vol. 4. Setúbal: SciTePress, 2021 - (Bracken, B.; Fred, A.; Gamboa, H.), (2021), s. 268-275. Biostec. ISBN 978-989-758-490-9.
[International Conference on Bio-inspired Systems and Signal Processing /14./ Biosignals 2021, Part of the International Joint Conference on Biomedical Engineering Systems and Technologies /14./ Biostec 2021. online (PT), 11.02.2021-13.02.2021]
R&D Projects: GA MŠMT(CZ) EF16_013/0001775
EU Projects: European Commission(XE) 813120 - INSPiRE-MED
Institutional support: RVO:68081731
Keywords : magnetic resonance spectroscopy * quantification * deep learning * machine learning
OECD category: Medical engineering
https://www.scitepress.org/Link.aspx?doi=10.5220/0010318502680275
Permanent Link: http://hdl.handle.net/11104/0321308File Download Size Commentary Version Access 103185.pdf 5 651.2 KB Publisher’s postprint open-access - 2.0540863 - ÚPT 2021 RIV CZ eng C - Conference Paper (international conference)
Shamaei, Amirmohammad
Deep learning for magnetic resonance spectroscopy quantification: A time frequency analysis approach.
Proceedings II of the 26th Conference student EEICT 2020. Brno: UNIV TECHNOLOGY, FAC ELECTRICAL ENG & COMMUNICATION, 2020, s. 131-135. ISBN 978-80-214-5868-0.
[Annual Conference on Student Electrical Engineering, Information Science and Communication Technologies (STUDENT EEICT) /26./. Brno (CZ), 23.04.2020-23.04.2020]
EU Projects: European Commission(XE) 813120 - INSPiRE-MED
Institutional support: RVO:68081731
Keywords : magnetic resonance spectroscop * quantification * deep learning * machine learning
OECD category: Atomic, molecular and chemical physics (physics of atoms and molecules including collision, interaction with radiation, magnetic resonances, Mössbauer effect)
https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2020_sbornik_2.pdf
Permanent Link: http://hdl.handle.net/11104/0318460File Download Size Commentary Version Access EEICT_2020_Shamaei.PDF 20 338.4 KB Author’s postprint open-access