Abstract
MRI has become an invaluable tool for diagnostic brain imaging, providing unrivalled qualitative and quantitative information to the radiologist. However, due to long scanning times and capital costs, access to MRI lags behind CT. Typical brain protocols lasting over 30 min set a clear limitation to patient experience, scanner throughput, operation profitability, and lead to long waiting times for an appointment.
As image quality, in terms of spatial resolution and noise, is strongly dependent on acquisition duration, significant scanning acceleration must successfully address challenging image degradation. In this work, we consider the scan acceleration scenario of a strongly anisotropic acquisition matrix. We propose a neural approach that jointly deblurs scan pairs acquired with mutually orthogonal phase encoding directions. This leverages the complementarity of the respective phase encoded information as blur directions are also mutually orthogonal between the scans in the pair. The proposed architecture, trained end-to-end, is applied to T1w scan pairs consisting of one scan with contrast media injection (CMI), and one without. Qualitative and quantitative validation is provided against state-of-the-art deblurring methods, for an acceleration factor of 4 beyond compressed sensing acceleration. The proposed method outperforms the compared methods, suggesting its possible clinical applicability for this challenging task.
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Acknowledgements
Gali Hod would like to thank the Israeli Ministry of Science and Technology for supporting her under the scholarship program during the research period.
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Hod, G. et al. (2023). Complementary Phase Encoding for Pair-Wise Neural Deblurring of Accelerated Brain MRI. In: Karlinsky, L., Michaeli, T., Nishino, K. (eds) Computer Vision – ECCV 2022 Workshops. ECCV 2022. Lecture Notes in Computer Science, vol 13803. Springer, Cham. https://doi.org/10.1007/978-3-031-25066-8_13
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