Presentation Details
A CONVOLUTIONAL NEURAL NETWORK ALGORITHM FOR CODED APERTURE IMAGING RECONTRUCTION
ID：49
View Protection：ATTENDEE
Updated Time：2024-09-23 20:32:20
Hits：333
Oral Presentation
Start Time：Pending（Asia/Shanghai）
Duration：Pending
Session：No Session »
Abstract
Coded aperture radiation imaging technology has been extensively applied in nuclear security, decommissioning of nuclear facilities, radioactive decontamination, and special nuclear material detection. However, in complex radioactive environment, common decoding algorithms have poor ability to suppress noise. In this paper, an reconstruction algorithm based on convolutional neural networks (CNN) is proposed. Additionally, the Geant4 software is utilized to simulate the process of encoded aperture imaging. Meanwhile numerical cut method was used to suppress noise. The reconstruction results show that the average CNR of orphan source reconstructed by the CNN method is 15.2, while that of the cross-correlation decoding algorithm and the dual cross-correlation decoding algorithm are 13.1 and 5.8, respectively. Moreover, after using numerical cut method, the CNN decoding algorithm can obtain ideal image reconstruction results for 94.2% of the radioactive sources in the field of view (FOV). When there are 5 radioactive sources in the FOV, the image reconstructed by cross-correlation decoding algorithm contains artifacts, while the CNN algorithm can accurately distinguish the source. Therefore, under complex conditions involving multiple radioactive sources, the convolutional neural network algorithm has stronger adaptability than the cross-correlation decoding algorithm and can perform more complex and accurate positioning.
Keywords
Coded Aperture Imaging (CAI),Monte Carlo simulation,Correlation Decoding Algorithms,Convolutional neural network algorithm (CNN)
Speaker
Xu Wenrui
Harbin Engineering University； Harbin；Fundamental Science on Nuclear Safety and Simulation Technology LaboratorySubmission Author
All Comments
Important Date
-
Conference Date
Sep 23
2024
toSep 25
2024
-
Sep 24 2024
Contribution Submission Deadline
-
Sep 25 2024
Registration deadline
Sponsored By
Harbin Engineering University (HEU)
Contact Information
- Prof. WANG Xiang
- xi******@hrbeu.edu.cn
Previous Conferences
-
2016-09-26 China Chengdu,China
8th International Symposium on Symbiotic Nuclear Power Systems for 21st Century -
2016-09-26 China Chengdu,China
8th International Symposium on Symbiotic Nuclear Power Systems for 21st Century -
2010-08-23 China 哈尔滨市
The 3rd International Symposium on Symbiotic Nuclear Power Systems for 21st Century (ISSNP2010)
Submit Comment