Multi-modal weighted quadratic priors for robust intensity independent synergistic PET-MR reconstruction

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Abstract

We propose a simple and robust synergistic PET-MR reconstruction algorithm using mutually-weighted quadratic priors. Maximum a-posteriori (MAP) objective functions were used for PET and MR reconstructions, including MAP expectation maximization (MAPEM) for PET and MAP sensitivity encoding (SENSE) for MR reconstruction. For both reconstructions, mutually-weighted quadratic priors were used for reduction of noise and artifacts, with preservation of PET-MR common boundaries. The weighting coefficients are updated from the current PET and MR estimates using normalized multi-modal Gaussian similarity kernels, which are in turn derived as the product of modality-specific kernels. Hence, the resulting kernels are independent of both signal intensities and contrast orientations. The performance of the proposed method was evaluated using 3D realistic simulations and a clinical FDG PET/T1-MPRAGE/FLAIR MR dataset. For simulations, undersampled MR reconstructions with undersampling factors of 4, 6 and 8 were considered while for the clinical dataset an MR undersampling factor of 4 was used. For PET reconstructions, the proposed method was compared with maximum likelihood expectation maximization (MLEM) and fully-sampled MR guided MAPEM (as a PET benchmark). For MR reconstructions, the proposed method was compared with fully-sampled reconstruction (as an MR benchmark), total variation (TV) regularized undersampled SENSE, and PET/FLAIR guided undersampled SENSE. Results showed that the proposed method can outperform conventional reconstructions especially for highly undersampled MR data, while preserving modality-unique features. For the clinical dataset, the proposed method showed promising results especially for PET reconstruction, in spite of the substantial PET-MR intensity and contrast differences. In summary, the proposed synergistic algorithm and priors offer a robust multi-modal synergistic image reconstruction framework.
Original languageEnglish
Title of host publicationIEEE NSS MIC Conference
PublisherIEEE
Publication statusAccepted/In press - 3 Jul 2017
Event2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Atlanta, United States
Duration: 21 Oct 201728 Oct 2017
http://www.nss-mic.org/2017/News.asp

Conference

Conference2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
Abbreviated titleIEEE NSS/MIC 2017
Country/TerritoryUnited States
CityAtlanta
Period21/10/201728/10/2017
Internet address

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