Related papers: Simulated Thick, Fully-Depleted CCD Exposures Anal…
The purpose of this project is to investigate the use of charge couple devices (CCDs) to detect electrons directly. This can be done in transmission electron microscopy (TEM) for electrons over 100 KeV, but for space plasma instruments,…
Dual-energy computed tomography (DECT) enables material-specific imaging through acquisitions at two different X-ray energy spectra. Material decomposition from DECT data is an ill-posed inverse problem that is highly sensitive to noise…
We introduce the fully-depleted charge-coupled device (CCD) as a particle detector. We demonstrate its low energy threshold operation, capable of detecting ionizing energy depositions in a single pixel down to 50 eVee. We present results of…
This study explores the use of charge-coupled devices (CCDs) for detecting low-energy beta particles from tritium decay - a critical signal for nuclear safety, nuclear nonproliferation, and environmental monitoring. We employ a dual…
Deep neural networks have received considerable attention in clinical imaging, particularly with respect to the reduction of radiation risk. Lowering the radiation dose by reducing the photon flux inevitably results in the degradation of…
Deep learning (DL) is an emerging analysis tool across sciences and engineering. Encouraged by the successes of DL in revealing quantitative trends in massive imaging data, we applied this approach to nano-scale deeply sub-diffractional…
Radiation-induced photocurrent in semiconductor devices can be simulated using complex physics-based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high-level…
Strongly correlated systems containing d/f-electrons present a challenge to conventional density functional theory (DFT), such as the widely used local density approximation (LDA) or generalized gradient approximation (GGA). In this work,…
X-ray photon-counting detectors (PCDs) are drawing an increasing attention in recent years due to their low noise and energy discrimination capabilities. The energy/spectral dimension associated with PCDs potentially brings great benefits…
We explore the use of deep learning to localise galactic structures in low surface brightness (LSB) images. LSB imaging reveals many interesting structures, though these are frequently confused with galactic dust contamination, due to a…
Thick fully depleted CCDs, while enabling wide spectral response, also present challenges in understanding the systematic errors due to 3D charge transport. This 2014 Workshop on Precision Astronomy with Fully Depleted CCDs covered progress…
In this paper, we present a deep learning-based (DL-based) algorithm, as a purely mathematical platform, for providing intuitive understanding of the properties of electromagnetic (EM) wave-matter interaction in nanostructures. This…
This report presents an overview of the unconventional use of charge-coupled devices (CCDs) to search for Dark Matter (DM). The DArk Matter In CCDs (DAMIC Experiment) employs the bulk silicon of thick, fully-depleted CCDs as a target for…
Dual energy computed tomography (DECT) has become of particular interest in clinic recent years. The DECT scan comprises two images, corresponding to two photon attenuation coefficients maps of the objects. Meanwhile, the DECT images are…
Photon counting detectors (PCDs) bring valuable advantages to diagnostic computed tomography (CT), including lower noise and higher resolution than energy integrating detectors. However, there are still several nonideal factors preventing…
Accurate and efficient cell detection is crucial in many biomedical image analysis tasks. We evaluate the performance of several Deep Learning (DL) methods for cell detection in Papanicolaou-stained cytological Whole Slide Images (WSIs),…
Recently, deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by…
The accuracy of the information that can be extracted from electron diffraction patterns is often limited by the presence of optical distortions. Existing distortion characterization techniques typically require knowledge of the reciprocal…
Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level…
In photoacoustic tomography (PAT), the acoustic pressure waves produced by optical excitation are measured by an array of detectors and used to reconstruct an image. Sparse spatial sampling and limited-view detection are two common…