AI Medical Compendium Topic:
Image Interpretation, Computer-Assisted

Clear Filters Showing 1081 to 1090 of 2720 articles

Selection, Visualization, and Interpretation of Deep Features in Lung Adenocarcinoma and Squamous Cell Carcinoma.

The American journal of pathology
Although deep learning networks applied to digital images have shown impressive results for many pathology-related tasks, their black-box approach and limitation in terms of interpretability are significant obstacles for their widespread clinical uti...

Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study.

The Lancet. Digital health
BACKGROUND: Geographic atrophy is a major vision-threatening manifestation of age-related macular degeneration, one of the leading causes of blindness globally. Geographic atrophy has no proven treatment or method for easy detection. Rapid, reliable,...

Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinic...

MRI-Based Machine Learning Prediction Framework to Lateralize Hippocampal Sclerosis in Patients With Temporal Lobe Epilepsy.

Neurology
BACKGROUND AND OBJECTIVES: MRI fails to reveal hippocampal pathology in 30% to 50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of co...

Visual Analytics for Hypothesis-Driven Exploration in Computational Pathology.

IEEE transactions on visualization and computer graphics
Recent advances in computational and algorithmic power are evolving the field of medical imaging rapidly. In cancer research, many new directions are sought to characterize patients with additional imaging features derived from radiology and patholog...

EAD-Net: A Novel Lesion Segmentation Method in Diabetic Retinopathy Using Neural Networks.

Disease markers
Diabetic retinopathy (DR) is a common chronic fundus disease, which has four different kinds of microvessel structure and microvascular lesions: microaneurysms (MAs), hemorrhages (HEs), hard exudates, and soft exudates. Accurate detection and countin...

Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning.

IEEE transactions on neural networks and learning systems
Medical imaging technologies, including computed tomography (CT) or chest X-Ray (CXR), are largely employed to facilitate the diagnosis of the COVID-19. Since manual report writing is usually too time-consuming, a more intelligent auxiliary medical s...

Object-Guided Instance Segmentation With Auxiliary Feature Refinement for Biological Images.

IEEE transactions on medical imaging
Instance segmentation is of great importance for many biological applications, such as study of neural cell interactions, plant phenotyping, and quantitatively measuring how cells react to drug treatment. In this paper, we propose a novel box-based i...

Multilevel Strip Pooling-Based Convolutional Neural Network for the Classification of Carotid Plaque Echogenicity.

Computational and mathematical methods in medicine
Carotid plaque echogenicity in ultrasound images has been found to be closely correlated with the risk of stroke in atherosclerotic patients. The automatic and accurate classification of carotid plaque echogenicity is of great significance for clinic...

Automated detection of superficial fungal infections from microscopic images through a regional convolutional neural network.

PloS one
Direct microscopic examination with potassium hydroxide is generally used as a screening method for diagnosing superficial fungal infections. Although this type of examination is faster than other diagnostic methods, it can still be time-consuming to...