Proton therapy monitoring method, device and system based on neural network

A neural network and proton technology, applied in the field of nuclear medicine imaging, can solve the problems of low measurement accuracy and low accuracy of proton therapy.

Inactive Publication Date: 2019-09-24
彭浩
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Problems solved by technology

[0005] In view of this, the purpose of the present invention is to provide a neural network-based proton therapy monitoring method, device and system to solve

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  • Proton therapy monitoring method, device and system based on neural network
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  • Proton therapy monitoring method, device and system based on neural network

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Embodiment Construction

[0061] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other implementations obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0062] figure 1 It is a flow chart of Embodiment 1 of the neural network-based proton therapy monitoring method of the present invention. Such as figure 1 As shown, the neural network-based proton therapy monitoring method of this embodiment may specifically include the following steps:

[0063] S101. Determine the tumor lesion area according to the pre-built three-dimensional phantom;

[0064] Firstly, the whole body of the patient is scanned by a CT machin...

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Abstract

The invention relates to a proton therapy monitoring method, device and system based on a neural network. The proton therapy monitoring method based on the neural network comprises the steps that according to a three-dimensional body model built in advance, a tumor lesion area is determined; after a proton beam shines the tumor lesion area, positive electron nuclide is measured in preset time to obtain distributed information of the positive electron nuclide; according to the distributed information, an image reconstruction algorithm is adopted to build a PET image; the PET image is input to a built neural network regression model and a neural network classification model, and dose distribution and range of the proton beam are determined; the position of a prague peak is determined according to the dose distribution and range; whether the position of the prague peak and the dose distribution conform to the preset proton therapy requirement or not is detected; and if not, beam out parameters of the proton beam are adjusted. By adopting the technical scheme of the proton therapy monitoring method based on the neural network, the influence of breathing and exercising of human body organs on the measurement can be reduced, the range of protons and the precision of the dose distribution are improved, and the accuracy of proton therapy is improved.

Description

technical field [0001] The invention relates to the technical field of nuclear medicine imaging, in particular to a neural network-based proton therapy monitoring method, device and system. Background technique [0002] Proton therapy is a cutting-edge radiotherapy technology for precise treatment of malignant tumors (cancer). During proton therapy, the irradiation dose curve of proton beams in the human body rises slowly at first, and then gradually increases until the maximum dose deposition occurs at the Bragg peak. Then the curve drops rapidly and tends to zero. The Bragg peak characteristic of the proton beam can make the tumor tissue receive the maximum irradiation dose, and at the same time, it can prevent the normal organs behind the tumor tissue from being damaged by radiation, and reduce the side effects of treatment. [0003] The advantages of proton therapy are as follows: 1) The dose at the proton Bragg peak is three to four times higher than the dose just ente...

Claims

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Application Information

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IPC IPC(8): A61N5/10
CPCA61N5/1064A61N2005/1087
Inventor 彭浩李中星王意昂
Owner 彭浩
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