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Robust CBCT reconstruction method based on low-rank tensor decomposition and total variational regularization

A technology of tensor decomposition and total variation, applied in 2D image generation, instruments, complex mathematical operations, etc., can solve the problems of image pollution, the introduction of staircase artifacts, the inefficiency of recovering lost data, etc., to reduce outliers The effect of achieving robustness and broad application prospects

Active Publication Date: 2022-04-15
WUHAN UNIV
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Problems solved by technology

However, real 2D projection images taken under low-dose conditions are sometimes contaminated by outliers such as readout noise (impulse noise)
At the same time, although the TV prior can effectively reduce Gaussian noise, it will introduce staircase artifacts
Also, when projection data is lost due to impulsive noise, it is not efficient to recover the lost data

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  • Robust CBCT reconstruction method based on low-rank tensor decomposition and total variational regularization
  • Robust CBCT reconstruction method based on low-rank tensor decomposition and total variational regularization
  • Robust CBCT reconstruction method based on low-rank tensor decomposition and total variational regularization

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[0044] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0045] Such as figure 1 As shown, this embodiment provides a CBCT reconstruction method under mixed Gaussian impulse noise, which specifically includes the following steps:

[0046] Step 1: By introducing the Huber loss function as a data fidelity item;

[0047] We project images from a series of 2D Its vector form is expressed as Reconstruction target, N is the total number of projection angles. In CBCT reconstruction we represent the target as a tensor Denotes the mapping of χ to y on the basis of the CBCT reconstruction process i The projection function of the ith corner of .

[0048] In the objective function, there are always two items, one is the data fidelity term, which models the statistics of the 2D projection data; the other is the p...

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Abstract

The present invention provides a robust CBCT reconstruction method based on low-rank tensor decomposition and total variation regularization, including: using the Huber loss function as a data fidelity item in CBCT reconstruction, so that the reconstruction can be performed under low radiation dose conditions for Impulse noise is robust; low-rank tensor properties are used as a prior term, which helps to restore structural information loss caused by impulse noise; by further integrating 3D TV prior terms to reduce the impact of Gaussian noise, Therefore, a CBCT reconstruction model is proposed; the optimization problem is solved by the alternate minimization method, and the reconstructed image is obtained and output. In the mixed state of Gaussian noise and impulse noise, the method of the invention can not only effectively eliminate the influence of noise, but also preserve edges well and reconstruct high-quality three-dimensional images.

Description

technical field [0001] The invention belongs to the technical field of image reconstruction, mainly relates to a CBCT reconstruction method under mixed Gaussian pulse noise, and is widely applicable to many clinical applications. Background technique [0002] Cone beam computed tomography (CBCT) technology is a new type of computed tomography (CT) technology, which is based on a cone-shaped X-ray beam centered on a two-dimensional detector, which can be rotated in different directions. Angle captures a series of two-dimensional projection images, and reconstructs the internal three-dimensional structure image of the object through a specific algorithm. Due to the characteristics of low cost, high resolution and short data acquisition time, CBCT technology plays an important role in numerous clinical applications. To reduce the impact of X-rays on patients, low radiation doses are recommended in most clinical applications. In this case, since the signal strength is relative...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T11/00G06F17/16
CPCG06T11/005G06F17/16
Inventor 田昕陈葳赵芳李波李松
Owner WUHAN UNIV
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