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Volume 11
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Article

Rosette Trajectory MRI Reconstruction with Vision Transformers

by
Muhammed Fikret Yalcinbas
1,*,
Cengizhan Ozturk
1,2,
Onur Ozyurt
3,
Uzay E. Emir
4 and
Ulas Bagci
5
1
Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Turkey
2
Center for Targeted Therapy Technologies (CT3), Boğaziçi University, Istanbul 34984, Turkey
3
Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2-0QQ, UK
4
Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
5
Machine and Hybrid Intelligence Lab, Northwestern University, Chicago, IL 60611, USA
*
Author to whom correspondence should be addressed.
Tomography 2025, 11(4), 41; https://doi.org/10.3390/tomography11040041
Submission received: 4 February 2025 / Revised: 12 March 2025 / Accepted: 14 March 2025 / Published: 1 April 2025
(This article belongs to the Topic AI in Medical Imaging and Image Processing)
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Abstract

Introduction: An efficient pipeline for rosette trajectory magnetic resonance imaging reconstruction is proposed, combining the inverse Fourier transform with a vision transformer (ViT) network enhanced with a convolutional layer. This method addresses the challenges of reconstructing high-quality images from non-Cartesian data by leveraging the ViT’s ability to handle complex spatial dependencies without extensive preprocessing. Materials and Methods: The inverse fast Fourier transform provides a robust initial approximation, which is refined by the ViT network to produce high-fidelity images. Results and Discussion: This approach outperforms established deep learning techniques for normalized root mean squared error, peak signal-to-noise ratio, and entropy-based image quality scores; offers better runtime performance; and remains competitive with respect to other metrics.
Keywords: MRI; machine learning; medical imaging MRI; machine learning; medical imaging

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MDPI and ACS Style

Yalcinbas, M.F.; Ozturk, C.; Ozyurt, O.; Emir, U.E.; Bagci, U. Rosette Trajectory MRI Reconstruction with Vision Transformers. Tomography 2025, 11, 41. https://doi.org/10.3390/tomography11040041

AMA Style

Yalcinbas MF, Ozturk C, Ozyurt O, Emir UE, Bagci U. Rosette Trajectory MRI Reconstruction with Vision Transformers. Tomography. 2025; 11(4):41. https://doi.org/10.3390/tomography11040041

Chicago/Turabian Style

Yalcinbas, Muhammed Fikret, Cengizhan Ozturk, Onur Ozyurt, Uzay E. Emir, and Ulas Bagci. 2025. "Rosette Trajectory MRI Reconstruction with Vision Transformers" Tomography 11, no. 4: 41. https://doi.org/10.3390/tomography11040041

APA Style

Yalcinbas, M. F., Ozturk, C., Ozyurt, O., Emir, U. E., & Bagci, U. (2025). Rosette Trajectory MRI Reconstruction with Vision Transformers. Tomography, 11(4), 41. https://doi.org/10.3390/tomography11040041

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