Accès libre

A systematic review of deep learning techniques for generating synthetic CT images from MRI data

Isaac Kwesi Acquah

Isaac Kwesi Acquah

  • Department of Medical Physics, University of GhanaGhana
  • Department of Physics Education, University of EducationWinneba, Ghana
Recherchez cet auteur sur
Sciendo|Google Scholar
Acquah, Isaac Kwesi
, 
Shiraz Issahaku

Shiraz Issahaku

  • Department of Medical Physics, University of GhanaGhana
  • Ghana Atomic Energy CommissionAccra, Ghana
Recherchez cet auteur sur
Sciendo|Google Scholar
Issahaku, Shiraz
 et 
Samuel Nii Adu Tagoe

Samuel Nii Adu Tagoe

  • Department of Medical Physics, University of GhanaGhana
  • Department of Radiation Oncology, National Centre for Radiotherapy and Nuclear Medicine, Korle-Bu Teaching HospitalGhana
Recherchez cet auteur sur
Sciendo|Google Scholar
Tagoe, Samuel Nii Adu
  
02 avr. 2025
A systematic review of deep learning techniques for generating synthetic CT images from MRI data's Cover Image
À propos de cet article
Article précédent
Article suivant
Citez
Télécharger la couverture
Publié en ligne: 02 avr. 2025
Pages: 20 - 38
Reçu: 17 sept. 2024
Accepté: 10 janv. 2025
DOI: https://doi.org/10.2478/pjmpe-2025-0003
Mots clés
© 2025 Isaac Kwesi Acquah et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Acquah, Isaac Kwesi
Department of Medical Physics, University of GhanaGhana
Department of Physics Education, University of EducationWinneba, Ghana
Issahaku, Shiraz
Department of Medical Physics, University of GhanaGhana
Ghana Atomic Energy CommissionAccra, Ghana
Tagoe, Samuel Nii Adu
Department of Medical Physics, University of GhanaGhana
Department of Radiation Oncology, National Centre for Radiotherapy and Nuclear Medicine, Korle-Bu Teaching HospitalGhana
Langue:
Anglais
Périodicité:
4 fois par an
Sujets de la revue:
Médecine, Génie biomédical, Physique, Physique technique et appliquée, Physique médicale
RSS Feed de la revue