AIMC Topic: Photons

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Deep learning-based material decomposition of iodine and calcium in mobile photon counting detector CT.

PloS one
Photon-counting detector (PCD)-based computed tomography (CT) offers several advantages over conventional energy-integrating detector-based CT. Among them, the ability to discriminate energy exhibits significant potential for clinical applications be...

Evaluation of monolithic crystal detector with dual-ended readout utilizing multiplexing method.

Physics in medicine and biology
Monolithic crystal detectors are increasingly being applied in positron emission tomography (PET) devices owing to their excellent depth-of-interaction (DOI) resolution capabilities and high detection efficiency. In this study, we constructed and eva...

Deep-Learning for Rapid Estimation of the Out-of-Field Dose in External Beam Photon Radiation Therapy - A Proof of Concept.

International journal of radiation oncology, biology, physics
PURPOSE: The dose deposited outside of the treatment field during external photon beam radiation therapy treatment, also known as out-of-field dose, is the subject of extensive study as it may be associated with a higher risk of developing a second c...

Neural network informed photon filtering reduces fluorescence correlation spectroscopy artifacts.

Biophysical journal
Fluorescence correlation spectroscopy (FCS) techniques are well-established tools to investigate molecular dynamics in confocal and super-resolution microscopy. In practice, users often need to handle a variety of sample- or hardware-related artifact...

Monolithic 2D Perovskites Enabled Artificial Photonic Synapses for Neuromorphic Vision Sensors.

Advanced materials (Deerfield Beach, Fla.)
Neuromorphic visual sensors (NVS) based on photonic synapses hold a significant promise to emulate the human visual system. However, current photonic synapses rely on exquisite engineering of the complex heterogeneous interface to realize learning an...

Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging.

Acta radiologica (Stockholm, Sweden : 1987)
This review article highlights the potential of integrating photon-counting computed tomography (CT) and deep learning algorithms in medical imaging to enhance diagnostic accuracy, improve image quality, and reduce radiation exposure. The use of phot...

Noise Suppression With Similarity-Based Self-Supervised Deep Learning.

IEEE transactions on medical imaging
Image denoising is a prerequisite for downstream tasks in many fields. Low-dose and photon-counting computed tomography (CT) denoising can optimize diagnostic performance at minimized radiation dose. Supervised deep denoising methods are popular but ...

Learnable latent embeddings for joint behavioural and neural analysis.

Nature
Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neu...

Multi-Scale Histogram-Based Probabilistic Deep Neural Network for Super-Resolution 3D LiDAR Imaging.

Sensors (Basel, Switzerland)
LiDAR (Light Detection and Ranging) imaging based on SPAD (Single-Photon Avalanche Diode) technology suffers from severe area penalty for large on-chip histogram peak detection circuits required by the high precision of measured depth values. In this...