Medical imaging method and system

Patent metadata

Field	Value
Publication number	US-11398012-B2
Application number	US-202016902330-A
Country	US
Kind code	B2
Filing date	Jun 16, 2020
Priority date	Jun 17, 2019
Publication date	Jul 26, 2022
Grant date	Jul 26, 2022

Abstract

The present application provides a medical imaging method and system and a non-transitory computer-readable storage medium. The medical imaging method comprises obtaining an original image acquired by an X-ray imaging system, and post-processing the original image based on a trained network to obtain an optimized image after processing.

First claim

The invention claimed is:

1. A medical imaging method, comprising:
obtaining an original image acquired by an X-ray imaging system; and
post-processing the original image based on a trained network to obtain an optimized image after processing;
wherein the network is trained based on a sample original image set and a target image set; and
wherein the training method comprises:
obtaining a plurality of original images acquired by the X-ray imaging system, so as to obtain the sample original image set;
separately post-processing the original images based on preferences of one or a plurality of users, so as to obtain a plurality of target image sets corresponding to preferences of each user; and
training a neural network by using the sample original image set as an input and each of the plurality of target image sets as an output, so as to obtain one or a plurality of networks corresponding to the preferences of each user.

2. The method according to claim 1 , wherein before post-processing the original image, the method further comprises inputting the original image to the network based on a first instruction of a user.

3. The method according to claim 2 , wherein the first instruction is triggered based on a first operating unit in an image display interface.

4. The method according to claim 1 , wherein the trained network comprises one or a plurality of networks, and the method further comprises:
selecting one from the one or a plurality of networks based on a second instruction of the user, so as to post-process the original image.

5. The method according to claim 4 , wherein the second instruction of the user is triggered based on identification of the user.

6. The method according to claim 4 , wherein the second instruction of the user is triggered based on a second operating unit in the image display interface.

7. The method according to claim 1 , further comprising:
further inputting the original image and the optimized image to the network based on a third instruction of the user, so as to optimize the network.

8. The method according to claim 7 , wherein the third instruction is triggered based on a third operating unit in the image display interface.

9. A non-transitory computer-readable storage medium for storing a computer program, wherein when executed by a computer, the computer program causes the computer to perform the medical imaging method according claim 1 .

10. A medical imaging system, comprising:
a control module, configured to obtain an original image acquired by an X-ray imaging system;
a post-processing module, configured to post-process the original image based on a trained network to obtain an optimized image after processing;
a display module, configured to display the original image and the optimized image; and
a training module, configured to train the network based on a sample original image set and a target image set;
wherein the training module is further configured to:
obtain a plurality of original images acquired by the X-ray imaging system, so as to obtain the sample original image set;
separately post-process the original images based on preferences of one or a plurality of users, so as to obtain a plurality of target image sets corresponding to preferences of each user; and
train a neural network by using the sample original image set as an input and each of the plurality of target image sets as an output, so as to obtain one or a plurality of networks corresponding to the preferences of each user.

11. The system according to claim 10 , wherein the display module comprises a first operating unit configured to generate a first instruction so as to input the original image to the network.

Assignees

• Ge Prec Healthcare Llc

Inventors

• Wang Dejun
• Ge Yaan
• Sun Yan
• Qi Buer
• Li Huanzhong

Classifications

• G06T12/30 Primary

  Image post-processing, e.g. metal artefact correction · CPC title

• A61B6/5211 Primary

  involving processing of medical diagnostic data · CPC title

• G06T5/50

  using two or more images, e.g. averaging or subtraction · CPC title

• G06T2207/20084

  Artificial neural networks [ANN] · CPC title

• G06T2207/20081

  Training; Learning · CPC title