Related papers: A Finely Segmented Semi-Monolithic Detector tailor…
The synergistic interpretation of anatomical information from computed tomography (CT) and metabolic information from positron emission tomography (PET) is important to oncologic imaging. However, existing deep learning methods for PET/CT…
A monolithic active pixel sensor based direct detector that is optimized for the primary beam energies in scanning electron microscopes is implemented for electron back-scattered diffraction (EBSD) applications. The high detection…
Crystal arrays made of LSO and LuAP crystals 2x2x10 mm pixels were manufactured for evaluation of detector with depth-of-interaction (DOI) determination capability intended for small animal positron emission tomograph. Position-sensitive…
Organic scintillators are widely used for fast neutron detection and spectroscopy. Several effects complicate the interpretation of results from detectors based upon these materials. First, fast neutrons will often leave a detector before…
This paper demonstrates a novel method to extract photomultiplier tube (PMT) calibration timing constants in large liquid scintillation detectors from physics data using the machinery of unsupervised deep learning. The approach uses a…
This paper describes the design and performance of a 50 liter, two-segment $^{6}$Li-loaded liquid scintillator detector that was designed and operated as prototype for the PROSPECT (Precision Reactor Oscillation and Spectrum) Experiment.…
The ClearMind project aims to develop the TOF-PET position sensitive detection module optimized for the time resolution, spatial resolution, and detection efficiency. For this, the ClearMind project uses a large (59 $\times$ 59 mm$^2$)…
Autonomous driving vehicles and robotic systems rely on accurate perception of their surroundings. Scene understanding is one of the crucial components of perception modules. Among all available sensors, LiDARs are one of the essential…
Purpose: Magnetic polarizability tensors (MPTs) provide an economical characterisation of conducting magnetic metallic objects and their spectral signature can aid in the solution of metal detection inverse problems, such as scrap metal…
Single Photon Emission Computed Tomography (SPECT) is a non-invasive imaging modality, frequently used in myocardial perfusion imaging. The biggest challenges facing the majority of clinical SPECT systems are low sensitivity, poor…
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…
FIB/SEM tomography represents an indispensable tool for the characterization of three-dimensional nanostructures in battery research and many other fields. However, contrast and 3D classification/reconstruction problems occur in many cases,…
We report on the spatial response characterization of large LaCl$_{3}$(Ce) monolithic crystals optically coupled to 8$\times$8 pixel silicon photomultiplier (SiPM) sensors. A systematic study has been carried out for 511 keV $\gamma$-rays…
Deep learning has revolutionized the accurate segmentation of diseases in medical imaging. However, achieving such results requires training with numerous manual voxel annotations. This requirement presents a challenge for whole-body…
The TT-PET collaboration is developing a small animal TOF-PET scanner based on silicon detectors featuring 30 ps RMS time resolution and intended to be inserted in an existing MRI scanner. The TT-PET scanner makes use of a stack of layers…
A novel beam profiler based on microstructured scintillation resin is presented. The detector consists of a bundle of waveguides, with an active area of 30 x 30 mm$^2$ and a pitch of 400 $\mu$m, obtained by molding a scintillating resin…
DEPFET pixel detectors are unique devices in terms of energy and spatial resolution because very low noise (ENC = 2.2e at room temperature) operation can be obtained by implementing the amplifying transistor in the pixel cell itself. Full…
Parameter-efficient fine-tuning (PEFT) is an effective methodology to unleash the potential of large foundation models in novel scenarios with limited training data. In the computer vision community, PEFT has shown effectiveness in image…
Purpose: To apply a convolutional neural network (CNN) to develop a system that segments intensity calibration phantom regions in computed tomography (CT) images, and to test the system in a large cohort to evaluate its robustness. Methods:…
CLICTD is a monolithic silicon pixel sensor fabricated in a modified 180 nm CMOS imaging process with a small collection electrode design and a high-resistivity epitaxial layer. It features an innovative sub-pixel segmentation scheme and is…