Medical image fusion with deep neural networks
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-58665-9
Abstract: Medical image fusion aims to fuse multiple images from a single or multiple imaging modes to enhance their corresponding clinical applications in diagnosing and evaluating medical problems, a trend that has attracted increasing attention. However,… read more here.
Keywords: salient components; image; medical image; fusion deep ... See more keywords
A Hybrid Adaptive Fusion Deep Learning Model for Fault Diagnosis of Rotating Machinery Under Noisy Conditions
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3572902
Abstract: Rotating machinery is essential in modern industry. A robust noise-resistant method is proposed to improve diagnostic accuracy under intense noise conditions. Initially, time-domain signals are transformed into the time-frequency domain using the Synchrosqueezing Short-Time Fourier… read more here.
Keywords: fusion deep; adaptive fusion; rotating machinery; hybrid adaptive ... See more keywords
Multiscaled Fusion of Deep Convolutional Neural Networks for Screening Atrial Fibrillation From Single Lead Short ECG Recordings
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2018.2858789
Abstract: Atrial fibrillation (AF) is one of the most common sustained chronic cardiac arrhythmia in elderly population, associated with a high mortality and morbidity in stroke, heart failure, coronary artery disease, systemic thromboembolism, etc. The early… read more here.
Keywords: atrial fibrillation; multiscaled fusion; deep convolutional; fusion deep ... See more keywords
Multi-Channel Fusion Deep Wavelet Spectrum Network for Epileptic Signal Classification.
Sign Up to like & getrecommendations! Published in 2025 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2025.3610433
Abstract: Recent developments in the detection of epilepsy and classification of seizures using electroencephalogram (EEG) signals have shown notable progress, yet they still face some challenges. For example, tensor decomposition techniques struggle with high computational demands,… read more here.
Keywords: classification; channel fusion; fusion deep; wavelet ... See more keywords
A fusion of deep neural networks and game theory for retinal disease diagnosis with OCT images
Sign Up to like & getrecommendations! Published in 2024 at "Journal of X-Ray Science and Technology"
DOI: 10.3233/xst-240027
Abstract: Retinal disorders pose a serious threat to world healthcare because they frequently result in visual loss or impairment. For retinal disorders to be diagnosed precisely, treated individually, and detected early, deep learning is a necessary… read more here.
Keywords: game theory; fusion deep; game; retinal disease ... See more keywords
OA-MEN: a fusion deep learning approach for enhanced accuracy in knee osteoarthritis detection and classification using X-Ray imaging
Sign Up to like & getrecommendations! Published in 2025 at "Frontiers in Bioengineering and Biotechnology"
DOI: 10.3389/fbioe.2024.1437188
Abstract: Background Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of osteoarthritis confronts challenges such as reduced sensitivity, subjective interpretation, and heightened… read more here.
Keywords: deep learning; knee osteoarthritis; fusion deep; model ... See more keywords