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Low-dose CT reconstruction method based on twin feedback network

A feedback network and low-dose technology, applied in the fields of medical image processing and computer vision, can solve the problems of low resolution of organ lesions and insufficient protection of CT details, and achieve the effect of easy data and easy construction

Pending Publication Date: 2020-10-02
DALIAN UNIV OF TECH
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Problems solved by technology

Due to the insufficient protection of CT details in the reconstruction process of existing methods, the resolution of organ lesions is low or artifacts are introduced

Method used

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  • Low-dose CT reconstruction method based on twin feedback network
  • Low-dose CT reconstruction method based on twin feedback network
  • Low-dose CT reconstruction method based on twin feedback network

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Embodiment Construction

[0049] The twin feedback network-based low-dose CT reconstruction method of the present invention will be described in detail below in conjunction with the embodiments and accompanying drawings.

[0050] A low-dose CT reconstruction method based on twin feedback network, the specific network structure is as follows figure 1 As shown, the method implementation includes the following steps:

[0051] The first step is to prepare the training data;

[0052] The training data includes two parts: simulated ellipse data and Mayo data. Both datasets contain low-dose images along with corresponding normal-dose images.

[0053] 1-1) Simulated ellipse data: We use the ODL library (Operator Discretization Library) in the Python language to make the data set. The data set is divided into training set and test set. The image size is 128X128 pixels. The training set contains 5000 normal Dose ellipse image and corresponding simulated low dose ellipse image pair. Referring to the Mayo data...

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Abstract

The invention discloses a low-dose CT reconstruction method based on a twin feedback network, and belongs to the field of medical image processing and computer vision. According to the invention, themethod comprises the steps: taking a low-dose CT image as input, acquiring a preliminary reconstruction result through a reconstruction branch of the twin feedback network, acquiring a boundary graphthrough a priori branch, continuously optimizing the network parameters through detail protection loss, and obtaining a final reconstruction result. The method is simple in program and easy to implement, and a high-resolution reconstruction result can be obtained in an end-to-end mode. The detail protection loss function designed by the invention can comprehensively realize CT image detail protection from two aspects of local and global aspects.

Description

technical field [0001] The invention belongs to the fields of medical image processing and computer vision, and in particular relates to a low-dose CT reconstruction method based on a twin feedback network for detail protection. Background technique [0002] At present, computed tomography (CT, Computed Tomography) has become a common imaging method for auxiliary diagnosis. However, in order to ensure sufficient clarity of CT images, the radiation risk of high-dose radiation to the human body cannot be underestimated. Most devices are designed to reduce the risk of cancer or genetic damage that may be brought about by high doses of radiation, leading to low-dose CT. How to solve the stronger noise and more artifacts brought about by reducing the radiation dose has become a challenging problem. Existing methods can be summarized into the following three categories: (1) Filtered reconstruction methods for CT sinograms: these methods design filters for sinograms to achieve re...

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Application Information

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IPC IPC(8): G06T11/00G06N3/04G06N3/08
CPCG06T11/003G06N3/08G06N3/045
Inventor 叶昕辰徐禹尧徐睿樊鑫
Owner DALIAN UNIV OF TECH
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