AI Medical Compendium Topic

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Impact of deep learning reconstructions on image quality and liver lesion detectability in dual-energy CT: An anthropomorphic phantom study.

Medical physics
BACKGROUND: Deep learning image reconstruction (DLIR) algorithms allow strong noise reduction while preserving noise texture, which may potentially improve hypervascular focal liver lesions.

AI integration into wavelength-based SPR biosensing: Advancements in spectroscopic analysis and detection.

Analytica chimica acta
BACKGROUND: In recent years, employing deep learning methods in the biosensing area has significantly reduced data analysis time and enhanced data interpretation and prediction accuracy. In some SPR fields, research teams have further enhanced detect...

Enhancement of structural and functional photoacoustic imaging based on a reference-inputted convolutional neural network.

Optics express
Photoacoustic microscopy has demonstrated outstanding performance in high-resolution functional imaging. However, in the process of photoacoustic imaging, the photoacoustic signals will be polluted by inevitable background noise. Besides, the image q...

Endpoint-aware audio-visual speech enhancement utilizing dynamic weight modulation based on SNR estimation.

Neural networks : the official journal of the International Neural Network Society
Integrating visual features has been proven effective for deep learning-based speech quality enhancement, particularly in highly noisy environments. However, these models may suffer from redundant information, resulting in performance deterioration w...

Neural-WDRC: A Deep Learning Wide Dynamic Range Compression Method Combined With Controllable Noise Reduction for Hearing Aids.

Trends in hearing
Wide dynamic range compression (WDRC) and noise reduction both play important roles in hearing aids. WDRC provides level-dependent amplification so that the level of sound produced by the hearing aid falls between the hearing threshold and the highes...

Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis.

Current oncology (Toronto, Ont.)
Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective ...

Deep Equilibrium Unfolding Learning for Noise Estimation and Removal in Optical Molecular Imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe no...

Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification.

PloS one
In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, de...

Generative adversarial networks with fully connected layers to denoise PPG signals.

Physiological measurement
The detection of arterial pulsating signals at the skin periphery with Photoplethysmography (PPG) are easily distorted by motion artifacts. This work explores the alternatives to the aid of PPG reconstruction with movement sensors (accelerometer and/...