Path-Planning System for Radioisotope Identification Devices Using 4π Gamma Imaging Based on Random Forest Analysis

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 12; p. 4325
• Main Authors: Tomita, Hideki, Hara, Shintaro, Mukai, Atsushi, Yamagishi, Keita, Ebi, Hidetake, Shimazoe, Kenji, Tamura, Yusuke, Woo, Hanwool, Takahashi, Hiroyuki, Asama, Hajime, Ishida, Fumihiko, Takada, Eiji, Kawarabayashi, Jun, Tanabe, Kosuke, Kamada, Kei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2022; MDPI
• Subjects: 4π gamma imaging; Algorithms; Cesium 137; Cesium isotopes; Decision trees; Gamma rays; Identification; Imaging systems; Investigations; Methods; Nuclear power plants; Path planning; Position measurement; Prediction models; Radiation; Radiation sources; radioisotope identification; Radioisotopes; random forest; Sensors; Simulation; Variables; Japan
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22124325

We developed a path-planning system for radiation source identification devices using 4π gamma imaging. The estimated source location and activity were calculated by an integrated simulation model by using 4π gamma images at multiple measurement positions. Using these calculated values, a prediction model to estimate the probability of identification at the next measurement position was created by via random forest analysis. The path-planning system based on the prediction model was verified by integrated simulation and experiment for a 137Cs point source. The results showed that 137Cs point sources were identified using the few measurement positions suggested by the path-planning system.