AIMC Topic: Photons

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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...

Photon-Counting Detector CT of the Brain Reduces Variability of Hounsfield Units and Has a Mean Offset Compared with Energy-Integrating Detector CT.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Distinguishing GM from WM is essential for CT of the brain. The recently established photon-counting detector (PCD)-CT technology uses a novel detection technique that might allow more precise measurement of tissue attenuation...

Beetle-inspired responsive photonic microgel assemblies for multi-sensing enhanced by machine learning.

Biosensors & bioelectronics
Bioinspired photonic hydrogels hold promise as sensors; however, their use in triple-analyte sensing optical devices has been minimally explored. Temperature, serum Fe levels, and X-ray doses are critical factors for predicting and monitoring medical...

Photon-counting micro-CT scanner for deep learning-enabled small animal perfusion imaging.

Physics in medicine and biology
In this work, we introduce a benchtop, turn-table photon-counting (PC) micro-computed tomography (CT) scanner and highlight its application for dynamic small animal perfusion imaging.Built on recently published hardware, the system now features a CdT...

Scatter and beam hardening effect corrections in pelvic region cone beam CT images using a convolutional neural network.

Radiological physics and technology
The aim of this study is to remove scattered photons and beam hardening effect in cone beam CT (CBCT) images and make an image available for treatment planning. To remove scattered photons and beam hardening effect, a convolutional neural network (CN...

Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy.

Proceedings of the National Academy of Sciences of the United States of America
Enhancing the reliability and reproducibility of optical microscopy by reducing specimen irradiance continues to be an important biotechnology target. As irradiance levels are reduced, however, the particle nature of light is heightened, giving rise ...

Photon-counting CT in cancer radiotherapy: technological advances and clinical benefits.

Physics in medicine and biology
Photon-counting computed tomography (PCCT) marks a significant advancement over conventional Energy-integrating detector CT systems. This review highlights PCCT's superior spatial and contrast resolution, reduced radiation dose, and multi-energy imag...

Bioconjugates of photon-upconversion nanoparticles with antibodies for the detection of prostate-specific antigen and p53 in heterogeneous and homogeneous immunoassays.

Nanoscale
Sensitive immunoassays for the detection of tumor biomarkers play an important role in the early diagnosis and therapy of cancer. Using luminescent nanomaterials as labels can significantly improve immunoassay performance, especially in terms of sens...

Noisy image segmentation based on synchronous dynamics of coupled photonic spiking neurons.

Optics express
The collective dynamics in neural networks is essential for information processing and has attracted much interest on the application in artificial intelligence. Synchronization is one of the most dominant phenomenon in the collective dynamics of neu...

Two-stage neural network via sensitivity learning for 2D photonic crystal bandgap maximization.

Applied optics
We propose a two-stage neural network method to maximize the bandgap of 2D photonic crystals. The proposed model consists of a fully connected deep feed-forward neural network (FNN) and U-Net, which are employed, respectively, to generate the shape f...