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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
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Acquah, Isaac Kwesi
, 
Shiraz Issahaku

Shiraz Issahaku

  • Department of Medical Physics, University of GhanaGhana
  • Ghana Atomic Energy CommissionAccra, Ghana
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Issahaku, Shiraz
 and 
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
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Tagoe, Samuel Nii Adu
  
Apr 02, 2025
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Published Online: Apr 02, 2025
Page range: 20 - 38
Received: Sep 17, 2024
Accepted: Jan 10, 2025
DOI: https://doi.org/10.2478/pjmpe-2025-0003
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© 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
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Medicine, Biomedical Engineering, Physics, Technical and Applied Physics, Medical Physics
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