Related papers: Detailed simulation for the ClearMind prototype de…

In this paper we investigate, with a detailed Monte-Carlo simulation based on Geant4, the novel approach [Nucl. Instrum. Methods A588 (2008) 457] to 3D imaging with photon scattering. A monochromatic and well collimated gamma beam is used…

The 21-cm signal from the Epoch of Reionization (EoR) is a powerful probe of the evolution of the Universe. However, accurate measurements of the EoR signal from radio interferometric observations are sensitive to efficient foreground…

We compare existing segmented plastic antineutrino detectors with our new geometrically improved design for antineutrino detection and light collection efficiency. The purpose of this study is to determine the most suitable design style for…

Photomultiplier tubes (PMTs) are widely used in particle experiments for photon detection. PMT waveform analysis is crucial for high-precision measurements of the position and energy of incident particles in liquid scintillator (LS)…

A combination Time Projection Chamber-Cherenkov prototype detector has been developed as part of the Detector R&D Program for a future Electron Ion Collider. The prototype was tested at the Fermilab test beam facility to provide a proof of…

Recent tests of a single module of the Jagiellonian Positron Emission Tomography system (J-PET) consisting of 30 cm long plastic scintillator strips have proven its applicability for the detection of annihilation quanta (0.511 MeV) with a…

Purpose: The integration of multimodal imaging into operating rooms paves the way for comprehensive surgical scene understanding. In ophthalmic surgery, by now, two complementary imaging modalities are available: operating microscope (OPMI)…

JUNO is designed to determine the neutrino mass ordering with an energy resolution of 3% at 1 MeV. In the real detector, however, deformations of the central stainless-steel structure during installation lead to deviations of the…

Objective: Image reconstruction in high resolution PET scanners with depth of interaction (DOI) capability is computationally challenging due to the high sampling in detector and image space. This study evaluates the use of a virtual…

PET is a functional imaging technique based on detection of annihilation photons following beta decay producing positrons. In this paper, we present the concept of a new PET system for preclinical applications consisting of a ring of twelve…

Positional single photon incidence response (P-SPIR) theory is researched in this paper to generate more accurate PSF-contained system matrix simply and quickly. The method has been proved highly effective to improve the spatial resolution…

Depth cameras are emerging as a cornerstone modality with diverse applications that directly or indirectly rely on measured depth, including personal devices, robotics, and self-driving vehicles. Although time-of-flight (ToF) methods have…

We are currently conceiving, through (MC) simulation, a multi-channel gamma detector array (TIARA for Time-of-flight Imaging ARrAy) for the online monitoring of protontherapy treatments. By measuring the Time-Of-Flight (TOF) between a beam…

This paper proposes a new convolutional neural network with multiscale processing for detecting ground-glass opacity (GGO) nodules in 3D computed tomography (CT) images, which is referred to as PiaNet for short. PiaNet consists of a…

The ability to synthesise Computed Tomography images - commonly known as pseudo CT, or pCT - from MRI input data is commonly assessed using an intensity-wise similarity, such as an L2-norm between the ground truth CT and the pCT. However,…

The joint detection and classification of RF signals has been a critical problem in the field of wideband RF spectrum sensing. Recent advancements in deep learning models have revolutionized this field, remarkably through the application of…

Object detection in adverse weather is critical for the safety of autonomous vehicles; however, the scarcity of labelled, real-world foggy data remains a significant bottleneck. In this paper, we propose Clear2Fog (C2F), an end-to-end,…

Recent applications of deep convolutional neural networks in medical imaging raise concerns about their interpretability. While most explainable deep learning applications use post hoc methods (such as GradCAM) to generate feature…

Presice measurements of the photons conversion points in the scintillators are required to achieve a high spatial resolution of the PET system. I have developed a new method of reconstruction of the depth-of-interaction information for PET…

The performance of object detection systems in automotive solutions must be as high as possible, with minimal response time and, due to the often battery-powered operation, low energy consumption. When designing such solutions, we therefore…