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Real-time patch-based medical image modality propagation by GPU computing

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Abstract

The synthesis of patient data of a certain medical image modality by applying an image processing pipeline starting from other modality is receiving a lot of interest recently, as it allows to save acquisition time and sometimes avoid radiation to the patient. An example of this is the creation of computerized tomography volumes from magnetic resonance imaging data, which can be useful for several applications such as electromagnetic simulations, cranial morphometry and attenuation correction in PET/MR systems. We present a fast patch-based algorithm for this purpose, implemented using graphics processing unit computing techniques and gaining up to \(\times\)15.9 of speedup against a multicore CPU solution and up to about \(\times\)75 against a single core CPU solution.

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Acknowledgments

This research has been partially supported by the Spanish Government Projects Refs. TIN2015-69542-C2-1-R and TE2012-39095, and the NVIDIA GPU Education Center Program.

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Authors and Affiliations

  1. C/Tulipán, S/N, 28933, Móstoles, Spain

    Eduardo Alcaín, Angel Torrado-Carvajal, Antonio S. Montemayor & Norberto Malpica

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  1. Eduardo Alcaín
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  2. Angel Torrado-Carvajal
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  3. Antonio S. Montemayor
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  4. Norberto Malpica
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Correspondence to Antonio S. Montemayor.

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Alcaín, E., Torrado-Carvajal, A., Montemayor, A.S. et al. Real-time patch-based medical image modality propagation by GPU computing. J Real-Time Image Proc 13, 193–204 (2017). https://doi.org/10.1007/s11554-016-0568-0

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