Generation of Synthetic CT from MRI for MRI-Based Attenuation Correction of Brain PET Images Using Radiomics and Machine Learning

Aug 5, 2026

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Accurate quantitative PET imaging in neurological studies depends on proper attenuation correction, while PET/MRI faces ongoing limitations because MRI intensities do not directly correspond to linear attenuation coefficients. This study generates patient-specific synthetic CT volumes, attenuation maps, and attenuation correction factor (ACF) sinograms with continuous values by combining machine learning, image processing, and voxel-based radiomics feature extraction. Brain MR data from ten healthy volunteers are used to derive synthetic CT, attenuation maps, and ACFs via LightGBM from radiomics- and image-processing feature maps, with ultralow-dose CT as reference. Qualitative and quantitative comparisons evaluate agreement with reference images, maps, and sinograms.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

AccessFree to download

Abstract

Background

Purpose

Methods

Results

University of Groningen Generation of synthetic CT from MRI for MRI-based attenuation correction of brain PET images using radiomics and machine learning Hoseinipourasl, Amin; Hossein-Zadeh, Gholam Ali; Sheikhzadeh, Peyman; Arabalibeik, Hossein; Alavijeh, Shaghayegh Karimi; Zaidi, Habib; Ay, Mohammad Reza Published in: Medical Physics DOI: 10.1002/mp.17867 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2025 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Hoseinipourasl, A. , Hossein-Zadeh, G. A. , Sheikhzadeh, P. , Arabalibeik, H. , Alavijeh, S. K. , Zaidi, H. , & Ay, M. R. (2025) . Generation of synthetic CT from MRI for MRI-based attenuation correction of brain PET images using radiomics and machine learning. Medical Physics, 52(6), 3772-3784. [https://doi.org/10.1002/mp.17867](https://doi.org/10.1002/mp.17867) Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons) . The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: [https://www.rug.nl/library/open-access/self-archiving-pure/taverne](https://www.rug.nl/library/open-access/self-archiving-pure/taverne)amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/U MCG research database (Pure): [http://www.rug. nl/research/portal. For technical reasons the](http://www.rug. nl/research/portal. For technical reasons the)[ ](http://www.rug. nl/research/portal. For technical reasons the)[number of authors shown on this cover page is limited to 10 maximum.](number of authors shown on this cover page is limited to 10 maximum.) Download date: 01-01-2026 Received: 12 August 2024 Revised: 18 April 2025 Accepted: 19 April 2025 DOI: 10.1002/mp.17867 RESEARCH ARTICLE Generation of synthetic CT from MRI for MRI-based attenuation correction of brain PET images using radiomics and machine learning Amin Hoseinipourasl1,2 Gholam-Ali Hossein-Zadeh3 Peyman Sheikhzadeh4 Hossein Arabalibeik5 Shaghayegh Karimi Alavijeh2 Habib Zaidi6,7,8,9 Mohammad Reza Ay1,2 1 Research Center for Molecular and Cellular Imaging (RCMCI), Advanced Medical Technologies and Equipment Institute (AMTEI), Tehran University of Medical Sciences (TUMS), Tehran, Iran 2 Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran 3 School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran 4 Nuclear Medicine Department, IKHC, Faculty of Medicine, Tehran University of Medical Science, Tehran, Iran 5 Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, IK Hospital Complex, Tehran, Iran 6 Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, Geneva, Switzerland 7 Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, Netherlands 8 Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark 9 University Research and Innovation Center, Óbuda University, Budapest, Hungary Correspondence Habib Zaidi, Geneva University Hospital, Radiology and Medical Informatics, Division of Nuclear Medicine and Molecular Imaging, Geneva

FAQs

Why is attenuation correction challenging in PET/MRI for brain imaging?

MRI-guided attenuation correction remains challenging because MRI intensities lack a direct relationship with linear attenuation coefficients needed for PET reconstruction.

What does the proposed method generate from MRI for PET attenuation correction?

It generates patient-specific synthetic CT volumes, attenuation maps, and attenuation correction factor (ACF) sinograms with continuous values.

How are the generated synthetic CT and attenuation products evaluated?

Ultralow-dose CT images from the same volunteers provide the reference, and qualitative and quantitative metrics compare synthetic CT, attenuation maps, and ACF sinograms against corresponding reference data.

Aug 5, 2026

Uploaded by Eden

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