AIMC Topic: Deep Learning

Clear Filters Showing 4621 to 4630 of 28423 articles

Accurate Airway Tree Segmentation in CT Scans via Anatomy-Aware Multi-Class Segmentation and Topology-Guided Iterative Learning.

IEEE transactions on medical imaging
Intrathoracic airway segmentation in computed tomography is a prerequisite for various respiratory disease analyses such as chronic obstructive pulmonary disease, asthma and lung cancer. Due to the low imaging contrast and noises execrated at periphe...

CNN-O-ELMNet: Optimized Lightweight and Generalized Model for Lung Disease Classification and Severity Assessment.

IEEE transactions on medical imaging
The high burden of lung diseases on healthcare necessitates effective detection methods. Current Computer-aided design (CAD) systems are limited by their focus on specific diseases and computationally demanding deep learning models. To overcome these...

Constraint-Aware Learning for Fractional Flow Reserve Pullback Curve Estimation From Invasive Coronary Imaging.

IEEE transactions on medical imaging
Estimation of the fractional flow reserve (FFR) pullback curve from invasive coronary imaging is important for the intraoperative guidance of coronary intervention. Machine/deep learning has been proven effective in FFR pullback curve estimation. How...

SSL-CPCD: Self-Supervised Learning With Composite Pretext-Class Discrimination for Improved Generalisability in Endoscopic Image Analysis.

IEEE transactions on medical imaging
Data-driven methods have shown tremendous progress in medical image analysis. In this context, deep learning-based supervised methods are widely popular. However, they require a large amount of training data and face issues in generalisability to uns...

Medical Transformer: Universal Encoder for 3-D Brain MRI Analysis.

IEEE transactions on neural networks and learning systems
Transfer learning has attracted considerable attention in medical image analysis because of the limited number of annotated 3-D medical datasets available for training data-driven deep learning models in the real world. We propose Medical Transformer...

Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective From the Time-Frequency Analysis.

IEEE transactions on neural networks and learning systems
The motor imagery (MI) classification has been a prominent research topic in brain-computer interfaces (BCIs) based on electroencephalography (EEG). Over the past few decades, the performance of MI-EEG classifiers has seen gradual enhancement. In thi...

Rectify ViT Shortcut Learning by Visual Saliency.

IEEE transactions on neural networks and learning systems
Shortcut learning in deep learning models occurs when unintended features are prioritized, resulting in degenerated feature representations and reduced generalizability and interpretability. However, shortcut learning in the widely used vision transf...

Applications of Artificial Intelligence in Choroid Visualization for Myopia: A Comprehensive Scoping Review.

Middle East African journal of ophthalmology
Numerous artificial intelligence (AI) models, including deep learning techniques, are being developed to segment choroids in optical coherence tomography (OCT) images. However, there is a need for consensus on which specific models to use, requiring ...

Diabetic retinopathy detection via deep learning based dual features integrated classification model.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundThe primary recognition of diabetic retinopathy (DR) is a pivotal requirement to prevent blindness and vision impairment. This deadly condition is identified by highly qualified professionals by examining colored retinal images.ObjectiveThe...

Improved fractional-order gradient descent method based on multilayer perceptron.

Neural networks : the official journal of the International Neural Network Society
The fractional-order gradient descent (FOGD) method has been employed by numerous scholars in Artificial Neural Networks (ANN), with its superior performance validated both theoretically and experimentally. However, current FOGD methods only apply fr...