AIMC Topic: Photons

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First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels.

Investigative radiology
OBJECTIVE: The aim of this study was to evaluate the image quality (IQ) and performance of an artificial intelligence (AI)-based computer-aided detection (CAD) system in photon-counting detector computed tomography (PCD-CT) for pulmonary nodule evalu...

Photonic spiking neural network based on excitable VCSELs-SA for sound azimuth detection.

Optics express
We propose a photonic spiking neural network (SNN) based on excitable vertical-cavity surface-emitting lasers with an embedded saturable absorber (VCSELs-SA) for emulating the sound azimuth detection function of the brain for the first time. Here, th...

Photonic human identification based on deep learning of back scattered laser speckle patterns.

Optics express
The analysis of the dynamics of speckle patterns that are generated when laser light is back scattered from a tissue has been recently shown as very applicable for remote sensing of various bio-medical parameters. In this work, we present how the ana...

Multi-material decomposition of spectral CT images via Fully Convolutional DenseNets.

Journal of X-ray science and technology
BACKGROUND: Spectral computed tomography (CT) has the capability to resolve the energy levels of incident photons, which has the potential to distinguish different material compositions. Although material decomposition methods based on x-ray attenuat...

Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification.

Integrative biology : quantitative biosciences from nano to macro
Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, and of those immunocompetent and infected ~10% will proceed to active tuberculosis (TB). Current diagnostics cannot definitively identify LTBI and prov...

Fully Convolutional DenseNets for Segmentation of Microvessels in Two-photon Microscopy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Segmentation of microvessels measured using two-photon microscopy has been studied in the literature with limited success due to uneven intensities associated with optical imaging and shadowing effects. In this work, we address this problem using a c...

Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology.

Neuron
Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed "blind," meaning that throughput for sa...

Models for predicting objective function weights in prostate cancer IMRT.

Medical physics
PURPOSE: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate c...