Radiation source intensity reconstruction method based on reverse particle transport

Abstract

The invention discloses a radiation source intensity reconstruction method based on reverse particle transport. The method comprises the following steps: establishing a particle reverse transport nuclear database; obtaining particle energy and intensity distribution information at a measurement device, and establishing a reverse Monte Carlo radiation transport calculation model in combination with initial source space distribution information, medium image information and measurement device information; sampling the source particles according to particle energy and intensity distribution information at the measurement equipment, and simulating the particles by using a Monte Carlo reverse transport method until the particles are transported to a radiation source; finally, performing reverse transport simulation on all particles, and carrying out normalization processing on particle intensity distribution information at the radiation source obtained through statistics to obtain particle source intensity distribution at the radiation source. According to the invention, particle source intensity distribution can be effectively obtained, and accurate radiation source inversion can be carried out.

Description

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AI Technical Summary

Benefits of technology

In this new technology, we use an algorithm called inverse MCMC (iteratively optimized) for accurately reproducing radioactive particles' movement within matter undergoing treatment or exposure. By doing these simulations, our system allows us to create detailed models of how they move inside materials such as plates used during radiotherapies. These modeling techniques help researchers better predict what will happen when exposed radionuclides are given off from different sources. Overall, this innovation improves the quality control process for producing effective treatments against cancer cells.

Problems solved by technology

Technological Problem: Current Radiation Dosage Distribution (RDD) analysis techniques have limitations due to factors like long-term exposure from X-ray devices or complicated geometry that may affect their performance over time. There has been an effort towards developing more efficient algorithms with improved resolution capabilities while also improving upon existing ones.

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