Noise-reduction reconstruction method and computer-readable storage medium for low-dose pet image

A low-dose, dose-based technology, applied in the field of positron emission computed tomography, can solve the problems of iterative reconstruction method difficult to adjust hyperparameters, contrast reduction, large amount of calculation, etc., to achieve the effect of preserving image details and contrast, and reducing noise

Active Publication Date: 2022-04-22
FMI MEDICAL SYST CO LTD
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Problems solved by technology

However, reducing the injection dose will lead to increased image noise, decreased contrast, and may eventually affect the doctor's diagnosis
Traditional image post-processing methods including BM3D, NLM, etc. usually lead to problems such as image over-smoothing and image contrast degradation
Common methods include iterative reconstruction methods, image post-processing, and deep learning methods. Iterative reconstruction methods are usually difficult to adjust hyperparameters and require a large amount of calculation
In addition, conventional noise reduction methods can only obtain a specific noise reduction effect

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  • Noise-reduction reconstruction method and computer-readable storage medium for low-dose pet image
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  • Noise-reduction reconstruction method and computer-readable storage medium for low-dose pet image

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[0032] The advantages of the present invention will be further elaborated below in conjunction with the accompanying drawings and specific embodiments.

[0033] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present disclosure as recited in the appended claims.

[0034] The terminology used in the present disclosure is for the purpose of describing particular embodiments only, and is not intended to limit the present disclosure. As used in this disclosure and the appended claims, the singular...

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Abstract

The present invention provides a low-dose PET image noise reduction reconstruction method and a computer-readable storage medium, which can effectively reduce the noise in the image and effectively retain the image details by combining the trained deep learning network and the personalized reference image And contrast, and make the quantitative error less than 10%, to achieve the purpose of high-quality low-dose PET images. And the present invention can realize personalized customized noise reduction effect according to each doctor's preference, so as to meet the different needs of different doctors.

Description

technical field [0001] The invention relates to the technical field of positron emission computed tomography, in particular to a noise reduction and reconstruction method for low-dose PET images and a computer-readable storage medium. Background technique [0002] Positron Emission Tomography (Positron Emission Tomography) is a relatively advanced clinical examination imaging technology in the field of nuclear medicine. By injecting radiotracer drugs into the human body, a pair of gamma rays produced by the decay of radionuclide in the drug can obtain the distribution map of the radioactive drug in the human body. General radioactive tracers are selected from substances necessary for the metabolism of biological life, such as glucose, protein, nucleic acid, fatty acid, labeled with short-lived radionuclides (such as 18F, 11C, etc.), after injecting into the human body, passing through the substance The aggregation in metabolism reflects the situation of life metabolic activ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T11/00G06T5/00G06N3/04G06N3/08
CPCG06T11/003G06T5/002G06N3/04G06N3/08G06T2207/10104
Inventor 周龙叶宏伟
Owner FMI MEDICAL SYST CO LTD
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