AI Medical Compendium Topic:
Tomography, Optical Coherence

Clear Filters Showing 361 to 370 of 762 articles

A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scans.

Medical image analysis
The objective quantification of retinal atrophy associated with age-related macular degeneration (AMD) is required for clinical diagnosis, follow-up, treatment efficacy evaluation, and clinical research. Spectral Domain Optical Coherence Tomography (...

Automated classification of coronary atherosclerotic plaque in optical frequency domain imaging based on deep learning.

Atherosclerosis
BACKGROUND AND AIMS: We developed a deep learning (DL) model for automated atherosclerotic plaque categorization using optical frequency domain imaging (OFDI) and performed quantitative and visual evaluations.

A deep learning-based model for characterization of atherosclerotic plaque in coronary arteries using optical coherence tomography  images.

Medical physics
PURPOSE: Coronary artery events are mainly associated with atherosclerosis in adult population, which is recognized as accumulation of plaques in arterial wall tissues. Optical Coherence Tomography (OCT) is a light-based imaging system used in cardio...

Deep Learning in Biomedical Optics.

Lasers in surgery and medicine
This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo mi...

Artificial intelligence extension of the OSCAR-IB criteria.

Annals of clinical and translational neurology
Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data ...

Detection of oedema on optical coherence tomography images using deep learning model trained on noisy clinical data.

Acta ophthalmologica
PURPOSE: To meet the demands imposed by the continuing growth of the Age-related macular degeneration (AMD) patient population, automation of follow-ups by detecting retinal oedema using deep learning might be a viable approach. However, preparing an...

Artificial intelligence for classifying uncertain images by humans in determining choroidal vascular running pattern and comparisons with automated classification between artificial intelligence.

PloS one
PURPOSE: Abnormalities of the running pattern of choroidal vessel have been reported in eyes with pachychoroid diseases. However, it is difficult for clinicians to judge the running pattern with high reproducibility. Thus, the purpose of this study w...

Microparticle-Based Biochemical Sensing Using Optical Coherence Tomography and Deep Learning.

ACS nano
Advancing continuous health monitoring beyond vital signs to biochemistry will revolutionize personalized medicine. Herein, we report a biosensing platform to achieve remote biochemical monitoring using microparticle-based biosensors and optical cohe...

Distinguishing retinal angiomatous proliferation from polypoidal choroidal vasculopathy with a deep neural network based on optical coherence tomography.

Scientific reports
This cross-sectional study aimed to build a deep learning model for detecting neovascular age-related macular degeneration (AMD) and to distinguish retinal angiomatous proliferation (RAP) from polypoidal choroidal vasculopathy (PCV) using a convoluti...

Effects of subthreshold nanosecond laser therapy in age-related macular degeneration using artificial intelligence (STAR-AI Study).

PloS one
PURPOSE: To investigate changes in retinal thickness, drusen volume, and visual acuity following subthreshold nanosecond laser (SNL) treatment in patients with age-related macular degeneration (ARMD).