Publication detail

Deep-MyoSeg: Deep learning-based approach for myocardium segmentation in clinical T1-MOLLI and T2-bSSFP maps

JAKUBÍČEK, R. VALESCO, C. HUA, A. FOTAKI, A. PRIETO, C. BOTNAR, R.

Original Title

Deep-MyoSeg: Deep learning-based approach for myocardium segmentation in clinical T1-MOLLI and T2-bSSFP maps

Type

abstract

Language

English

Original Abstract

SMRA 2022 conference abstract as a result of cooperation with a foreign institution, Deep-MyoSeg: Deep learning-based approach for myocardium segmentation in clinical T1-MOLLI and T2-bSSFP maps

Keywords

myocardium segmentation

Authors

JAKUBÍČEK, R.; VALESCO, C.; HUA, A.; FOTAKI, A.; PRIETO, C.; BOTNAR, R.

Released

28. 8. 2022

Location

The Society for Magnetic Resonance Angiography (SMRA), Los Angeles, Spojené státy americké

Pages from

100

Pages to

100

Pages count

1

URL

https://society4mra.org/index.php/download/smra-2022-abstract-2/

BibTex

@misc{BUT178958,
  author="Roman {Jakubíček} and Carlos Jimeno {Valesco} and Alina {Hua} and Anastasia {Fotaki} and Claudia {Prieto} and Rene {Botnar}",
  title="Deep-MyoSeg: Deep learning-based approach for myocardium segmentation in clinical T1-MOLLI and T2-bSSFP maps",
  booktitle="ABSTRACT BOOK - SMRA 2022 -34th Annual International Conference
Solving clinical problems with human creativity and machine learning
",
  year="2022",
  pages="100--100",
  address="The Society for Magnetic Resonance Angiography (SMRA), Los Angeles, Spojené státy americké",
  url="https://society4mra.org/index.php/download/smra-2022-abstract-2/",
  note="abstract"
}