Method for training post-processing device for denoising MRI image and computing device for the same
AssigneeSeoul National University R&Db Foundation
InventorsJongho Lee, Juhyung Park
Life of this patent
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Abstract
Disclosed is a training method including outputting an MRI signal from a plurality of coils included in an MRI scanner and performing, by a computing device, supervised learning on a post-processing part included in the computing device by using, as training input data, a first image generated using a first group of coils among the plurality of coils and using, as a label, a second image generated using a second group of coils among the plurality of coils.
Claims7
A magnetic resonance imaging (MRI) system comprising:
- an MRI scanner including a first group of coils and a second group of coils;
- and
- a computing device including a post-processing part for post-processing an MRI image and a training management part,
- wherein the computing device is configured to:
- generate a first MRI image based on a first group of MRI signals obtained from the first group of coils, the first MRI image being used as training input data for supervised learning of the post-processing part, and
- generating a label image based on a second group of MRI signals obtained from the second group of coils, the label image being used as a label for supervised learning of the post-processing part, and
- wherein the training management part is configured to perform supervised learning on the post-processing part using the training input data and the label,
- wherein the first MRI image and the label image are obtained through a same one-time data acquisition process performed by the MRI scanner.
A neural network training method for training a post-processing part configured to receive an input of a magnetic resonance imaging (MRI) image and denoise the MRI image, the method comprising:
- generating, by an MRI scanner including a first group of coils and a second group of coils, a first MRI image based on a first group of MRI signals obtained from the first group of coils;
- generating, by the MRI scanner, a label image based on a second group of MRI signals obtained from the second group of coils;
- and
- performing, by a computing device, supervised learning on the post-processing part by using the first MRI image as training input data for supervised learning of the post-processing part and using the image as a label for supervised learning of the post-processing part,
- wherein the first image and the label image are obtained through a same one-time data acquisition process performed by the MRI scanner.
Dependencies are inferred from the claim text.