AI Medical Compendium Topic

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Image Interpretation, Computer-Assisted

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Adaptive Dual-Axis Style-Based Recalibration Network With Class-Wise Statistics Loss for Imbalanced Medical Image Classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Salient and small lesions (e.g., microaneurysms on fundus) both play significant roles in real-world disease diagnosis under medical image examinations. Although deep neural networks (DNNs) have achieved promising medical image classification perform...

Weakly supervised nuclei segmentation based on pseudo label correction and uncertainty denoising.

Artificial intelligence in medicine
Nuclei segmentation plays a vital role in computer-aided histopathology image analysis. Numerous fully supervised learning approaches exhibit amazing performance relying on pathological image with precisely annotations. Whereas, it is difficult and t...

A novel hybrid feature fusion approach using handcrafted features with transfer learning model for enhanced skin cancer classification.

Computers in biology and medicine
Skin cancer is a deadly disease and has the highest rising rates globally. It arises from aberrant skin cells, which are often caused by prolonged exposure to ultraviolet rays from sunlight or artificial tanning devices. Dermatologists rely on visual...

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images.

BMC medical informatics and decision making
Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imbalance, and computat...

Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI.

Computers in biology and medicine
This paper introduces a novel convolutional neural network model with an attention mechanism to advance Alzheimer disease (AD) classification using Magnetic Resonance Imaging (MRI). The model architecture is meticulously crafted to enhance feature ex...

Automated assessment of skin histological tissue structures by artificial intelligence in cutaneous melanoma.

Pathology, research and practice
BACKGROUND: Prognostic histopathological features such as mitosis in melanoma are excluded from the staging systems due to inter-observer variability and time constraints. While digital pathology offers artificial intelligence-driven solutions, exist...

Hybrid deep learning framework for diabetic retinopathy classification with optimized attention AlexNet.

Computers in biology and medicine
Diabetic retinopathy (DR) is a chronic condition associated with diabetes that can lead to vision impairment and, if not addressed, may progress to irreversible blindness. Consequently, it is essential to detect pathological changes in the retina to ...

Advanced imaging techniques and artificial intelligence in pleural diseases: a narrative review.

European respiratory review : an official journal of the European Respiratory Society
BACKGROUND: Pleural diseases represent a significant healthcare burden, affecting over 350 000 patients annually in the US alone and requiring accurate diagnostic approaches for optimal management. Traditional imaging techniques have limitations in d...

A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection.

Scientific reports
The most widespread kind of cancer, affecting millions of lives is skin cancer. When the condition of illness worsens, the chance of survival is reduced, and thus detection of skin cancer is extremely difficult. Hence, this paper introduces a new mod...

Deep Learning-Accelerated Non-Contrast Abbreviated Liver MRI for Detecting Malignant Focal Hepatic Lesions: Dual-Center Validation.

Korean journal of radiology
OBJECTIVE: To compare a deep learning (DL)-accelerated non-enhanced abbreviated MRI (AMRI) protocol with standard AMRI (AMRI) of the liver in terms of image quality and malignant focal lesion detection.