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Photons

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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...

A machine learning method for fast and accurate characterization of depth-of-interaction gamma cameras.

Physics in medicine and biology
Measuring the depth-of-interaction (DOI) of gamma photons enables increasing the resolution of emission imaging systems. Several design variants of DOI-sensitive detectors have been recently introduced to improve the performance of scanners for posit...

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...

Photon Optimizer (PO) prevails over Progressive Resolution Optimizer (PRO) for VMAT planning with or without knowledge-based solution.

Journal of applied clinical medical physics
The enhanced dosimetric performance of knowledge-based volumetric modulated arc therapy (VMAT) planning might be jointly contributed by the patient-specific optimization objectives, as estimated by the RapidPlan model, and by the potentially improved...

NEURAL NETWORK MODELLING OF CARDIAC DOSE CONVERSION COEFFICIENT FOR ARBITRARY X-RAY SPECTRA.

Radiation protection dosimetry
In this article, an approach to compute the dose conversion coefficients (DCCs) is described for the computational voxel phantom 'High-Definition Reference Korean-Man' (HDRK-Man) using artificial neural networks (ANN). For this purpose, the voxel pha...

A neural network-based method for spectral distortion correction in photon counting x-ray CT.

Physics in medicine and biology
Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the ot...

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...