Detail publikace

DEEP LEARNING FOR MAGNETIC RESONANCE SPECTROSCOPY QUANTIFICATION: A TIME-FREQUENCY ANALYSIS APPROACH

SHAMAEI, A.

Originální název

DEEP LEARNING FOR MAGNETIC RESONANCE SPECTROSCOPY QUANTIFICATION: A TIME-FREQUENCY ANALYSIS APPROACH

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

In this study, we verify the hypothesis that deep learning in combination with time-frequency analsis can be used for metabolite quantification and yeilds results more robust than deep learning trained with magnetic resonance signals in the frequency domain.

Klíčová slova

magnetic resonance spectroscopy ,quantification, deep learning, machine learning

Autoři

SHAMAEI, A.

Vydáno

23. 4. 2020

Nakladatel

Brno university of technology

Místo

Brno

ISBN

978-80-214-5868-0

Kniha

Proceeding 2 of 26th Conference student EEICT 2020

Edice

1

Číslo edice

2

Strany od

131

Strany do

135

Strany počet

5

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2020_sbornik_2.pdf

BibTex

@inproceedings{BUT164779,
  author="Amirmohammad {Shamaei}",
  title="DEEP LEARNING FOR MAGNETIC RESONANCE SPECTROSCOPY QUANTIFICATION: A TIME-FREQUENCY ANALYSIS APPROACH",
  booktitle="Proceeding 2 of 26th Conference student EEICT 2020",
  year="2020",
  series="1",
  number="2",
  pages="131--135",
  publisher="Brno university of technology",
  address="Brno",
  isbn="978-80-214-5868-0",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2020_sbornik_2.pdf"
}