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Systems and methods for magnetic resonance imaging standardization using deep learning

A magnetic resonance and imaging technology, which is applied in the direction of using nuclear magnetic resonance imaging system for measurement, neural learning methods, magnetic resonance measurement, etc., to achieve the effect of improving reproducibility and improving the accuracy of diagnosis

Pending Publication Date: 2021-02-02
长沙微妙医疗科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This task can be challenging as each manufacturer's images show different contrast or distortion due to different design considerations
Clinical imaging trials can be more challenging if multiple vendor scanners are involved

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  • Systems and methods for magnetic resonance imaging standardization using deep learning
  • Systems and methods for magnetic resonance imaging standardization using deep learning
  • Systems and methods for magnetic resonance imaging standardization using deep learning

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Embodiment Construction

[0017] While various embodiments of the invention have been shown and described herein, it will be readily understood by those skilled in the art that these embodiments are provided by way of example only. Numerous variations, changes and substitutions may occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed.

[0018] A need is recognized herein to transform magnetic resonance (MR) images from one vendor's appearance to another or a standardized MR style. The methods and systems of the present disclosure may be capable of transforming MR images acquired from different MR scanners into a composite or normalized form. The synthesized or normalized form may be a target form with predetermined characteristics, such as contrast, resolution, image size, color, skewness, distortion, orientation, and the like. Alternatively or additionally, the ta...

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Abstract

A computer-implemented method for transforming magnetic resonance (MR) imaging across multiple vendors is provided. The method comprises: obtaining a training dataset, wherein the training dataset comprises a paired dataset and an un-paired dataset, and wherein the training dataset comprises image data acquired using two or more MR imaging devices; training a deep network model using the trainingdataset; obtaining an input MR image; and transforming the input MR image to a target image style using the deep network model.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to U.S. Provisional Application No. 62 / 685,774, filed June 15, 2018, which is hereby incorporated in its entirety in its entirety. Background technique [0003] A common task for radiologists is to compare sequential imaging studies acquired on different magnetic resonance (MR) hardware systems. This task can be challenging as each manufacturer's images show different contrast or distortion due to different design considerations. Clinical imaging trials can be more challenging if multiple vendor scanners are involved. Therefore, it is desirable to transform MR images from one vendor's appearance to another vendor's appearance or a standardized MR style. Contents of the invention [0004] The present disclosure provides methods and systems capable of transforming magnetic resonance (MR) images from one vendor's appearance to another vendor's appearance or a standardized MR image forma...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06V10/764
CPCG06N3/088G06V2201/03G06V10/82G01R33/5608G06V10/764G06N3/045G06F18/2413G01R33/54G06N3/04G06T7/0012G06T2207/10088G06T2207/20081
Inventor 宫恩浩张涛格雷戈里·扎哈尔丘克
Owner 长沙微妙医疗科技有限公司