PET Image Reconstruction using Joint MR-PET Dictionary

Simultaneous magnetic resonance imaging (MRI) and positron emission tomography (PET) enable simultaneous acquisition of anatomical and functional imaging. Currently, separate reconstruction of MRI and PET images is performed. Recently, joint reconstruction of MRI-PET has been explored using gradient based priors, which have the risk of infusing cross-modality artefacts. We propose a coupled MR-PET patch based dictionary prior for the joint reconstruction of MRI and PET contrasts.

[1]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[2]  Leslie Ying,et al.  Sparsity-based PET image reconstruction using MRI learned dictionaries , 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

[3]  H. Jadvar,et al.  Competitive advantage of PET/MRI. , 2014, European journal of radiology.

[4]  Pawel Markiewicz,et al.  PET Reconstruction With an Anatomical MRI Prior Using Parallel Level Sets , 2016, IEEE Transactions on Medical Imaging.

[5]  P. Green.  Bayesian reconstructions from emission tomography data using a modified EM algorithm. , 1990, IEEE transactions on medical imaging.

[6]  Kristian Bredies,et al.  Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer , 2017, IEEE Transactions on Medical Imaging.

[7]  Andrew J Reader,et al.  Patch-based image reconstruction for PET using prior-image derived dictionaries , 2016, Physics in medicine and biology.

[8]  L. Shepp,et al.  Maximum Likelihood Reconstruction for Emission Tomography , 1983, IEEE Transactions on Medical Imaging.