Invention Grant
- Patent Title: Generalized approximate message passing algorithms for sparse magnetic resonance imaging reconstruction
- Patent Title (中): 用于稀疏磁共振成像重建的广义近似消息传递算法
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Application No.: US14630712Application Date: 2015-02-25
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Publication No.: US09542761B2Publication Date: 2017-01-10
- Inventor: Jin Tan , Boris Mailhe , Qiu Wang , Mariappan S. Nadar
- Applicant: Jin Tan , Boris Mailhe , Qiu Wang , Mariappan S. Nadar
- Applicant Address: DE Erlangen
- Assignee: Siemens Healthcare GmbH
- Current Assignee: Siemens Healthcare GmbH
- Current Assignee Address: DE Erlangen
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06T11/00 ; G06T7/00 ; A61B6/00

Abstract:
A method for reconstructing magnetic resonance imaging data includes acquiring a measurement dataset using a magnetic resonance imaging device and determining an estimated image dataset based on the measurement dataset. An iterative reconstruction process is performed to refine the estimated image dataset. Each iteration of the iterative reconstruction process comprises: updating the measurement dataset and a sparse coefficient dataset based on the estimated image dataset and a plurality of belief propagation terms, incorporating a noise prior dataset into the measurement dataset, incorporating a sparsity prior dataset into the sparse coefficient dataset, updating the plurality of belief propagation terms based on the measurement dataset and the sparsity prior dataset, and updating the estimated image dataset based on the plurality of belief propagation terms. A reconstructed image and confidence map are generated using the estimated image dataset.
Public/Granted literature
- US20160247299A1 Generalized Approximate Message Passing Algorithms for Sparse Magnetic Resonance Imaging Reconstruction Public/Granted day:2016-08-25
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