Prema izvještaju Instituta za medicinska istraživanja, koncentracija stroncija-90 u Gospiću porasla je s [...]

パナソニックは、同社美顔器で最高となる6MHzの変調型RF(ラジオ波)を搭載した美顔器「バイタリフト RF LUXE EH-SR90」を11月上旬に発売する。価格はオープン。直販価格は99,000円。

2026/9/15 （2026/9/16 更新）

YouTube video by New York Post

YouTube video by Moe Ququ

We evaluate the performance of an Omnivision OV5647 CMOS image sensor (5 Mp) for detecting radiation from Sr90 and Cs137 sources. Our experimental setup uses a Raspberry Pi 3 mini-computer for data acquisition, with image processing using Python and OpenCV libraries. We specify the necessary settings to convert a standard camera into a particle detector sensitive to electrons and photons, including a two-step background filtering procedure. In addition, we implement the first detailed Geant4 simulation that describes the layered geometry and material composition of a commercial CMOS sensor along with the radioactive sources. To enhance the simulation, we include an algorithm for charge diffusion and conversion of the energy deposited by electrons and photons into ADC counts. Our measurements are presented in terms of cluster size, the maximum ADC signal per cluster, and the number of clusters as a function of distance. We find a good agreement between the experimental data and simulation for all these observables, and we can reproduce the correlation between cluster size and maximum ADC signal per cluster. Thus, this simulation, cross-checked with data, can be used to test the feasibility of further particle detection ideas without the need to implement an experimental setup. However, the sensor has limited primary energy resolution and is thus unable to distinguish between different radioactive sources. Nevertheless, given the accurate measurement of energy deposition, the sensor, once calibrated, is suitable for dosimetric measurements of source activities.

We evaluate the performance of an Omnivision OV5647 CMOS image sensor (5 Mp) for detecting radiation from Sr90 and Cs137 sources. Our experimental setup uses a Raspberry Pi 3 mini-computer for data acquisition, with image processing using Python and OpenCV libraries. We specify the necessary settings to convert a standard camera into a particle detector sensitive to electrons and photons, including a two-step background filtering procedure. In addition, we implement the first detailed Geant4 simulation that describes the layered geometry and material composition of a commercial CMOS sensor along with the radioactive sources. To enhance the simulation, we include an algorithm for charge diffusion and conversion of the energy deposited by electrons and photons into ADC counts. Our measurements are presented in terms of cluster size, the maximum ADC signal per cluster, and the number of clusters as a function of distance. We find a good agreement between the experimental data and simulation for all these observables, and we can reproduce the correlation between cluster size and maximum ADC signal per cluster. Thus, this simulation, cross-checked with data, can be used to test the feasibility of further particle detection ideas without the need to implement an experimental setup. However, the sensor has limited primary energy resolution and is thus unable to distinguish between different radioactive sources. Nevertheless, given the accurate measurement of energy deposition, the sensor, once calibrated, is suitable for dosimetric measurements of source activities.