AIMC Topic: Tomography, Optical Coherence

Clear Filters Showing 11 to 20 of 857 articles

Improve deep learning-based reconstruction of optical coherence tomography angiography by siamese U-Net.

Biomedical physics & engineering express
Optical coherence tomography angiography (OCTA), as a functional imaging based on OCT, has found successful medical applications. OCTA produces vasculature imaging using blood flow motion as an intrinsic contrast agent. To date, the prevailing OCTA a...

Artificial intelligence-driven diagnosis for age-related macular degeneration bridging pathology and engineering: a survey.

International ophthalmology
Age-related macular degeneration (AMD) is the primary reason for severe visual impairments, making early diagnosis critically important. This paper provides a comprehensive review of the methods used to support screening and diagnostic decisions, foc...

Investigating the capability of deep learning models to predict age and biological sex from anterior segment ophthalmic imaging: a multi-centre retrospective study.

BMJ open
OBJECTIVE: To assess the capability of a convolutional neural network trained by transfer learning on anterior segment optical coherence tomography (AS-OCT) images, Placido-disk corneal topography images and external photographs to predict age and bi...

Benchmarking diffusion models against state-of-the-art architectures for OCT fluid biomarker segmentation.

PloS one
OBJECTIVES: Retinal diseases, major causes of vision impairment and blindness, are assessed using optical coherence tomography (OCT) scans. Automated report generation for retinal OCT scans, powered by deep learning, can help standardize interpretati...

Segmentation of Structural Components of Atherosclerotic Plaques on OCT Images Using Deep Machine Learning.

Kardiologiia
Aim        To develop an optimal method for automated segmentation of atherosclerotic plaque structural components in optical coherence tomography (OCT) images using an ensemble of deep learning neural network models based on a comparison of nine art...

Denoising diffusion-based anterior segment optical coherence tomography (AS-OCT) image generation.

International ophthalmology
PURPOSE: This study aims to address the scarcity of annotated Anterior Segment Optical Coherence Tomography (AS-OCT) datasets in ophthalmology by using Denoising Diffusion Generative Adversarial Networks (DD-GANs) to generate synthetic AS-OCT images ...

Retinal microvascular differences between multiple sclerosis and neuromyelitis optica spectrum disorder: a cross-sectional study with diagnostic modeling.

Journal of neurology
BACKGROUND AND OBJECTIVES: Retinal alterations in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) remain unclear, especially the specific patterns and extent of microvascular change. This study aimed to compare these altera...

A robust deep learning classifier for screening multiple retinal diseases on optical coherence tomography.

Scientific reports
Retinal diseases are among the leading causes of visual impairment worldwide, where timely diagnosis and management are critical to prevent irreversible vision loss and blindness, especially in regions with limited access to ophthalmologists. While a...

A comprehensive overview: deep learning approaches to central serous chorioretinopathy diagnosis.

BMC ophthalmology
PURPOSE: To synthesize evidence on deep learning applications for diagnosing central serous chorioretinopathy (CSCR), a macular disorder associated with vision loss, this systematic review categorized studies by diagnostic task and imaging modality. ...

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry.

Scientific reports
To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monitoring. Real-world da...