An investigation of γ radiation detection with a CMOS imaging sensor.

In this study, a feasibility of γ radiation detection using complementary metal-oxide semiconductor (CMOS) image sensors with a neural network algorithm to extract the γ rays interacted pixels has been investigated. The responses characteristics of the CMOS imaging sensor to γ-ray is studied by placed in a γ fields produced by standardCo orCs isotope sources. The supported preview frame rate of the CMOS image sensor is 25 fps, establishing the functional relationship between the gray level histograms and the dose rate through the neural network, the high energy γ-ray fromCo andCs source radiation dose rate in µSv/h level can be detected using the CMOS imaging sensor. The results show that the proposed method can effectively identify the number of photon particles which detected by the radiation monitoring system based on CMOS image sensor, and infer that the CMOS imaging sensor with a radiation signal extraction algorithm can be used as a dose warner for radiation protection purpose.