AI Medical Compendium Topic

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Tomography, Optical Coherence

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[Artificial intelligence in assessment of individual risks of age-related macular degeneration progression].

Vestnik oftalmologii
Age-related macular degeneration (AMD) is a progressive degenerative retinal disease and a leading cause of blindness in older adults worldwide. According to numerous studies, the number of affected individuals reached 196 million in 2020, with proje...

[Primary angle closure suspects: application of machine learning method for substantiation of close monitoring].

Vestnik oftalmologii
UNLABELLED: One of the priority areas in healthcare is the concept of predictive, preventive and personalized medicine, which is based on an individualized approach to the patient, including before the onset of diseases such as glaucoma.

Automated learning of glaucomatous visual fields from OCT images using a comprehensive, segmentation-free 3D convolutional neural network model.

Scientific reports
A segmentation-free 3D Convolutional Neural Network (3DCNN) model was adopted to estimate Visual Field (VF) in glaucoma cases using Optical Coherence Tomography (OCT) images. This study, conducted at a university hospital, included 6335 participants ...

Detection of diabetic macular oedema patterns with fine-grained image categorisation on optical coherence tomography.

BMJ open ophthalmology
PURPOSE: To develop an artificial intelligence (AI) system for detecting pathological patterns of diabetic macular oedema (DME) with fine-grained image categorisation using optical coherence tomography (OCT) images.

EFCNet enhances the efficiency of segmenting clinically significant small medical objects.

Scientific reports
Efficient segmentation of small hyperreflective dots, key biomarkers for diseases like macular edema, is critical for diagnosis and treatment monitoring.However, existing models, including Convolutional Neural Networks (CNNs) and Transformers, strugg...

Global-Local Transformer Network for Automatic Retinal Pathological Fluid Segmentation in Optical Coherence Tomography Images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: As a pivotal biomarker, the accurate segmentation of retinal pathological fluid such as intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelial detachment (PED), was a critical task for diagnosis and treatme...

The potential of artificial intelligence reading label system on the training of ophthalmologists in retinal diseases, a multicenter bimodal multi-disease study.

BMC medical education
OBJECTIVE: To assess the potential of artificial intelligence reading label system on the training of ophthalmologists in a multicenter bimodal multi-disease study.

Machine Learning-Based Immuno-Inflammatory Index Integrating Clinical Characteristics for Predicting Coronary Artery Plaque Rupture.

Immunity, inflammation and disease
BACKGROUND: Coronary artery plaque rupture (PR) is closely associated with immune-inflammatory responses. The systemic inflammatory index (SII) and the systemic inflammatory response index (SIRI) have shown potential in predicting the occurrence of P...

Deep learning segmentation of periarterial and perivenous capillary-free zones in optical coherence tomography angiography.

Journal of biomedical optics
SIGNIFICANCE: Automated segmentation of periarterial and perivenous capillary-free zones (CFZs) in optical coherence tomography angiography (OCTA) can significantly improve early detection and monitoring of diabetic retinopathy (DR), a leading cause ...