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Image artifact removal model and training method and system thereof

A model training and image technology, applied in the field of medical image processing, can solve the problems of unconsidered, the effect of removing artifacts needs to be improved, and the accuracy and comprehensiveness of the model are difficult to improve, so as to improve the generalization ability.

Pending Publication Date: 2021-11-23
SHANGHAI UNITED IMAGING HEALTHCARE
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Problems solved by technology

However, the current existing models do not consider the relevant information of the artifacts (such as the size of the artifacts, the material of the artifacts, etc.), making it difficult to improve the accuracy and comprehensiveness of the model, and the effect of removing artifacts needs to be improved

Method used

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  • Image artifact removal model and training method and system thereof
  • Image artifact removal model and training method and system thereof
  • Image artifact removal model and training method and system thereof

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Embodiment Construction

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the following briefly introduces the drawings that need to be used in the description of the embodiments. Apparently, the accompanying drawings in the following description are only some examples or embodiments of this specification, and those skilled in the art can also apply this specification to other similar scenarios. Unless otherwise apparent from context or otherwise indicated, like reference numerals in the figures represent like structures or operations.

[0021] It should be understood that "system", "device", "unit" and / or "module" as used herein is a method for distinguishing different components, elements, parts, parts or assemblies of different levels. However, the words may be replaced by other expressions if other words can achieve the same purpose.

[0022] As indicated in the specification and claims, the terms "a", "an", "an" and / or "the" are...

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Abstract

The embodiment of the invention provides an image artifact removal model training method and system. The method comprises the steps of obtaining a first initial image, and a preliminary correction image and an objective feature map corresponding to the first initial image; and inputting the first initial image, the preliminary correction image and the objective feature map into an image artifact removal model, taking the first initial image as a first training sample, taking a standard artifact-removed image corresponding to the first initial image as a first label, and adjusting parameters of the image artifact removal model through the objective feature map and the first label, and obtaining a trained image artifact removal model.

Description

technical field [0001] This specification relates to the field of medical image processing, in particular to an image artifact removal model and its training method and system. Background technique [0002] In medical imaging (such as CT imaging), metal objects have higher attenuation characteristics and stronger absorption of photons than human tissues. When X-rays pass through metal objects, it can cause beam hardening, and noise, volume effect and scattering effects are exacerbated. These effects lead to metallic artifacts in the reconstructed image. Machine learning models can be used to reduce or eliminate artifacts in reconstructed images. However, the current existing models do not consider the relevant information of artifacts (eg, the size of the artifacts, the material of the artifacts, etc.), making it difficult to improve the accuracy and comprehensiveness of the model, and the effect of removing artifacts needs to be improved. [0003] Therefore, it is desira...

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Application Information

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IPC IPC(8): G06T5/00G06K9/62G16H30/20
CPCG16H30/20G06T2207/10081G06T2207/20081G06F18/214G06T5/80G06T5/73G06T11/008G06V10/778G06V10/774G06V10/30G16H30/40G06T2211/441G06T2211/448
Inventor 李彪刘炎炎
Owner SHANGHAI UNITED IMAGING HEALTHCARE
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