Invention Grant
- Patent Title: System and method for deep learning-based generation of true contrast images utilizing synthetic magnetic resonance imaging data
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Application No.: US17344274Application Date: 2021-06-10
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Publication No.: US11808832B2Publication Date: 2023-11-07
- Inventor: Sudhanya Chatterjee , Dattesh Dayanand Shanbhag
- Applicant: GE PRECISION HEALTHCARE LLC
- Applicant Address: US WI Wauwatosa
- Assignee: GE Precision Healthcare LLC
- Current Assignee: GE Precision Healthcare LLC
- Current Assignee Address: US WI Wauwatosa
- Agency: Fletcher Yoder P.C.
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G01R33/565 ; G06N3/084

Abstract:
A computer-implemented method for generating an artifact corrected reconstructed contrast image from magnetic resonance imaging (MRI) data is provided. The method includes inputting into a trained deep neural network both a synthesized contrast image derived from multi-delay multi-echo (MDME) scan data or the MDME scan data acquired during a first scan of an object of interest utilizing a MDME sequence and a composite image, wherein the composite image is derived from both the MDME scan data and contrast scan data acquired during a second scan of the object of interest utilizing a contrast MRI sequence. The method also includes utilizing the trained deep neural network to generate the artifact corrected reconstructed contrast image based on both the synthesized contrast image or the MDME scan data and the composite image. The method further includes outputting from the trained deep neural network the artifact corrected reconstructed contrast image.
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