- Patent Title: Quality of medical images using multiple-contrast and deep learning
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Application No.: US16152185Application Date: 2018-10-04
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Publication No.: US10467751B2Publication Date: 2019-11-05
- Inventor: Greg Zaharchuk , Enhao Gong , John M. Pauly
- Applicant: The Board of Trustees of the Leland Stanford Junior University
- Applicant Address: US CA Stanford
- Assignee: The Board of Trustees of the Leland Stanford Junior University
- Current Assignee: The Board of Trustees of the Leland Stanford Junior University
- Current Assignee Address: US CA Stanford
- Agency: Lumen Patent Firm
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06T3/60 ; G06T5/00 ; G06T5/20 ; G06T5/50

Abstract:
A method of improving diagnostic and functional imaging is provided by obtaining at least two input images of a subject, using a medical imager, where each input image includes a different contrast, generating a plurality of copies of the input images using non-local mean (NLM) filtering, using an appropriately programmed computer, where each input image copy of the subject includes different spatial characteristics, obtaining at least one reference image of the subject, using the medical imager, where the reference image includes imaging characteristics that are different form the input images of the subject, training a deep network model, using data augmentation on the appropriately programmed computer, to adaptively tune model parameters to approximate the reference image from an initial set of the input and reference images, with the goal of outputting an improved quality image of other sets of low SNR low resolution images, for analysis by a physician.
Public/Granted literature
- US20190035078A1 Quality of Medical Images Using Multi-Contrast and Deep Learning Public/Granted day:2019-01-31
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