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US 2023/0410313 A1Published application
Image data processing to increase follow-up analysis fidelity
AssigneeGE Precision Healthcare LLC
InventorRaz Carmi
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Abstract
Techniques are provided for improving image data quality, such as in functional imaging follow-up studies, using reconstruction, post-processing, and/or deep-learning enhancement approaches in a way that automatically improves analysis fidelity, such as lesion tracking fidelity. The disclosed approaches may be useful in improving the performance of automatic analysis methods as well as in facilitating reviews performed by clinician.
Claims5
An image processing system, the image processing system comprising:
- one or more memory structures storing processor-executable code;
- and
- one or more processors in communication with the one or more memory structures, wherein the processor-executable code, when executed by the one or more processors, cause the one or more processors to perform acts comprising:
- training a deep learning network model for image enhancement by iteratively performing steps comprising:
- receiving a first input image volume and a second input image volume;
- providing the first input image volume and the second input image volume to the deep learning network model, wherein the deep learning network model is configured to respectively output a first output image volume and a second output image volume;
- comparing the first output image volume and the second output image volume based on a fidelity metric comprising a measure of structural similarity, wherein a loss function for the deep learning network model is based on the fidelity metric and training the deep learning network model is based on reduction or minimization of the loss function.
4 more elements
Dependencies are inferred from the claim text.