Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer

Knoll F, Holler M, Koesters T, Otazo R, Bredies K, Sodickson DK (2017)

Publication Type: Journal article

Publication year: 2017

Journal

IEEE Transactions on Medical Imaging Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 36

Pages Range: 1-16

Article Number: 7466848

Journal Issue: 1

DOI: 10.1109/TMI.2016.2564989

Abstract

While current state of the art MR-PET scanners enable simultaneous MR and PET measurements, the acquired data sets are still usually reconstructed separately. We propose a new multi-modality reconstruction framework using second order Total Generalized Variation (TGV) as a dedicated multi-channel regularization functional that jointly reconstructs images from both modalities. In this way, information about the underlying anatomy is shared during the image reconstruction process while unique differences are preserved. Results from numerical simulations and in-vivo experiments using a range of accelerated MR acquisitions and different MR image contrasts demonstrate improved PET image quality, resolution, and quantitative accuracy.

Authors with CRIS profile

Florian Knoll

Involved external institutions

New York University (NYU) US United States (USA) (US) Karl-Franzens-Universität Graz AT Austria (AT)

How to cite

APA:

Knoll, F., Holler, M., Koesters, T., Otazo, R., Bredies, K., & Sodickson, D.K. (2017). Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer. IEEE Transactions on Medical Imaging, 36(1), 1-16. https://doi.org/10.1109/TMI.2016.2564989

MLA:

Knoll, Florian, et al. "Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer." IEEE Transactions on Medical Imaging 36.1 (2017): 1-16.

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