AIMC Topic: Convolutional Neural Networks

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Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans.

Journal of neuroscience methods
BACKGROUND: The hippocampus plays a crucial role in memory and is one of the first structures affected by Alzheimer's disease. Postmortem MRI offers a way to quantify the alterations by measuring the atrophy of the inner structures of the hippocampus...

Enhancing Recommender Systems through Imputation and Social-Aware Graph Convolutional Neural Network.

Neural networks : the official journal of the International Neural Network Society
Recommendation systems are vital tools for helping users discover content that suits their interests. Collaborative filtering methods are one of the techniques employed for analyzing interactions between users and items, which are typically stored in...

WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in MR spectroscopic imaging.

Magnetic resonance in medicine
PURPOSE: Proton magnetic resonance spectroscopic imaging ( -MRSI) provides noninvasive spectral-spatial mapping of metabolism. However, long-standing problems in whole-brain -MRSI are spectral overlap of metabolite peaks with large lipid signal fro...

Computerized classification method for significant coronary artery stenosis on whole-heart coronary MRA using 3D convolutional neural networks with attention mechanisms.

Radiological physics and technology
This study aims to develop a computerized classification method for significant coronary artery stenosis on whole-heart coronary magnetic resonance angiography (WHCMRA) images using a 3D convolutional neural network (3D-CNN) with attention mechanisms...

Fluorescence images of skin lesions and automated diagnosis using convolutional neural networks.

Photodiagnosis and photodynamic therapy
In recent years, interest in applying deep learning (DL) to medical diagnosis has rapidly increased, driven primarily by the development of Convolutional Neural Networks and Transformers. Despite advancements in DL, the automated diagnosis of skin ca...

Two-dimensional identification of lower limb gait features based on the variational modal decomposition of sEMG signal and convolutional neural network.

Gait & posture
BACKGROUND: Gait feature recognition is crucial to improve the efficiency and coordination of exoskeleton assistance. The recognition methods based on surface electromyographic (sEMG) signals are popular. However, the recognition accuracy of these me...

A 4D tensor-enhanced multi-dimensional convolutional neural network for accurate prediction of protein-ligand binding affinity.

Molecular diversity
Protein-ligand interactions are the molecular basis of many important cellular activities, such as gene regulation, cell metabolism, and signal transduction. Protein-ligand binding affinity is a crucial metric of the strength of the interaction betwe...

Automated identification of impact spatters and fly spots with a residual neural network.

Forensic science international
In criminal investigations, distinguishing between impact spatters and fly spots presents a challenge due to their morphological similarities. Traditional methods of bloodstain pattern analysis (BPA) rely significantly on the expertise of professiona...

Optimizing convolutional neural networks for Chronic Obstructive Pulmonary Disease detection in clinical computed tomography imaging.

Computers in biology and medicine
We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD) based on emphysema presence in the lung with convolutional neural networks (CNN) by exploring manually adjusted versus automated window-setting optimization (WSO)...

Human activity recognition utilizing optimized attention induced Multihead Convolutional Neural Network with Mobile Net V1 from Mobile health data.

Network (Bristol, England)
Human Activity Recognition (HAR) systems are designed to continuously monitor human behaviour, mainly in the areas of entertainment and surveillance in intelligent home environments. In this manuscript, Human Activity Recognition utilizing optimized ...