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Low-dose CT reconstruction method based on double-domain interleaving network

An interwoven network, low-dose technology, applied in the fields of medical image processing and computer vision, can solve the problems of unadjustable results and noise that cannot be handled well, and achieve the effect of easy construction

Active Publication Date: 2021-08-13
TAIYUAN UNIV OF TECH
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Since the existing method does not have a good combination for the sinogram, which makes the noise generated in the process of reconstructing the image from the sinogram cannot be well processed, and the result is not adjustable, the present invention overcomes the shortcomings of the prior art, Provides a low-dose CT reconstruction method based on a dual-domain interleaving network to achieve adjustable reconstruction results, and can generate reconstruction results with different denoising levels through one network

Method used

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  • Low-dose CT reconstruction method based on double-domain interleaving network
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  • Low-dose CT reconstruction method based on double-domain interleaving network

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Embodiment Construction

[0052] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer, the present invention will be further described in detail in combination with the embodiments and accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. The technical solutions of the present invention will be described in detail below in conjunction with the embodiments and accompanying drawings, but the scope of protection is not limited thereto.

[0053] A low-dose CT reconstruction method based on a dual-domain interleaving network to achieve adjustable reconstruction results. The specific network structure is as follows: figure 1 As shown, the method implementation includes the following steps:

[0054] The first step is to prepare the training data:

[0055] The training data includes two parts: Osaka pulmonary dis...

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Abstract

The invention discloses a low-dose CT reconstruction method based on a double-domain interleaving network, and belongs to the field of medical image processing and computer vision. According to the method, a low-dose CT image and a corresponding sinogram are used as input, a distortion branch, a perception branch and a fusion branch are trained respectively in two stages, and learnable parameters are used for balancing distortion and perception; the method is simple in procedure and easy to implement, and reconstruction results better meeting diagnosis requirements of doctors can be obtained in an end-to-end mode; according to the invention, an adjustable reconstruction result can be generated through one network, the corresponding reconstruction result can be freely selected for the CT image with non-uniform noise distribution, and the lesion texture and organ structure of the CT image are protected while the overall perception effect is ensured.

Description

technical field [0001] The invention belongs to the technical fields of medical image processing and computer vision, and in particular relates to a low-dose CT reconstruction method based on a dual-domain interleaving network to realize adjustable reconstruction results. Background technique [0002] At present, computed tomography (CT, Computed Tomography) has become a common imaging method for auxiliary diagnosis. However, in order to ensure that CT images are clear enough, the radiation risk of high-dose radiation to the human body cannot be underestimated. Most of the equipment is designed to reduce the risk of cancer or genetic damage that may be brought about by high-dose radiation, making low-dose CT emerge as the times require. How to solve the stronger noise and more artifacts brought about by reducing the radiation dose has become a challenging problem. [0003] Existing methods can be summarized into the following three categories: (1) Filtering and reconstruct...

Claims

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Application Information

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IPC IPC(8): G06T11/00G06N3/04G06N3/08
CPCG06T11/005G06N3/08G06N3/045
Inventor 李窦哲李灯熬赵菊敏赵红燕李付江李朋伟
Owner TAIYUAN UNIV OF TECH
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