Photon Counting Imaging with an Electron-Bombarded Pixel Image Sensor

Parallel processing of radiation measurements and radiation video optimization

In this study, we propose a parallel processing method for analyzing video-image radiation-response signals and suppressing radiation noise. We studied the linear-representation law of various image-information components on the radiation dose rate. Subsequently, the simulation images were used to examine the response-signal extract and radiation-noise suppression. The results indicate that the majority of response signals in the global image comprise forward superposition. The peak signal-to-noise ratio of the red channel was significantly improved when the noise signal-substitution algorithm and median filter were applied successively. Real-time radiation dose-rate measurements and clear images under irradiation can be obtained simultaneously.

Ultrawide-range radiation detection based on dynamic identification and analysis of the response of a monolithic active pixel sensor

In this paper, we present an ultrawide-range radiation detection method based on dynamic recognition and analysis of the response signal of a monolithic active pixel sensor (MAPS). Our analysis of the MAPS response mechanism determined that adaptive adjustment of the sensor's integral time is key to quantification of ionizing radiation in an ultrawide range. We also determined that different data processing methods are required for accurate quantification of high and low radiation dose rates. The results of experiments conducted after calibration demonstrate that our technique is capable of radiation detection across five orders of magnitude (ranging from milligrays per hour to hundreds of grays per hour), with errors of less than 5%. Chip-based nuclear radiation detection can be realized using our technique, enabling MAPS to be used as a supplement to traditional detectors in characterization of unknown and complex radiation environments.

Strong Radiation Field Online Detection and Monitoring System with Camera

Herein, we report the γ-ray ionizing radiation response of a commercial monolithic active-pixel sensor (MAPS) camera under strong-dose-rate irradiation with an online detection and monitoring system for strong radiation conditions. We present the first results of the distribution of three types of MAPS camera and establish a linear relationship between the average response signal and radiation dose rate in the strong-dose-rate range. There is an obvious response signal in the video frames when the camera module parameters are set to automatic, but the linear response is very poor. However, the fixed image parameters are not good at adapting to the changes of the environment and affect the quality of the video frames. A dual module online radiation detection and monitoring probe was made to carry out effective video monitoring and radiation detection at the same time. The measurement results show that the dose rate detection error is less than 5% with a dose rate in the range of 60 to 425 Gy/h, and the visible light image does not have obvious distortion, deformation, or color shift due to the interference of the radiation response event and radiation damage. Hence, the system test results show that it can be used for online detection and monitoring in a strong radiation environment.

Wide-field time-correlated single photon counting-based fluorescence lifetime imaging microscopy

Wide-field time-correlated single photon counting detection techniques, where the position and the arrival time of the photons are recorded simultaneously using a camera, have made some advances recently. The technology and instrumentation used for this approach is employed in areas such as nuclear science, mass spectroscopy and positron emission tomography, but here, we discuss some of the wide-field TCSPC methods, for applications in fluorescence microscopy. We describe work by us and others as presented in the Ulitima fast imaging and tracking conference at the Argonne National Laboratory in September 2018, from phosphorescence lifetime imaging (PLIM) microscopy on the microsecond time scale to fluorescence lifetime imaging (FLIM) on the nanosecond time scale, and highlight some applications of these techniques.

A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image

An Intensified Charge-Coupled Device (ICCD) image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a) Different from the independent identically distributed (i.i.d.) noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b) The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image.