AIMC Topic: Tomography, Optical Coherence

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Prediction of textile pilling resistance using optical coherence tomography.

Scientific reports
This paper describes a new method of textile pilling prediction, based on multivariate analysis of the spatial layer above the surface. The original idea of the method is the acquisition of 3D fabric image using optical coherence tomography (OCT) wit...

[Future of interventional cardiology : Does everything revolve around AI and robotics?].

Herz
In recent years, software-assisted imaging systems, such as computed tomography, have contributed to the improvement of noninvasive options for the diagnostics of coronary heart disease (CHD). In addition, the possibilities of individual morphologica...

Prior optic neuritis detection on peripapillary ring scans using deep learning.

Annals of clinical and translational neurology
BACKGROUND: The diagnosis of multiple sclerosis (MS) requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes...

Randomised controlled trial on robot-assisted versus manual surgery for pucker peeling.

Clinical & experimental ophthalmology
BACKGROUND: The aim was to explore the feasibility and safety of performing common surgical steps in epiretinal membrane (ERM) peeling using the Preceyes Surgical System (PSS).

Measurement of retinal nerve fiber layer thickness with a deep learning algorithm in ischemic optic neuropathy and optic neuritis.

Scientific reports
This work aims at determining the ability of a deep learning (DL) algorithm to measure retinal nerve fiber layer (RNFL) thickness from optical coherence tomography (OCT) scans in anterior ischemic optic neuropathy (NAION) and demyelinating optic neur...

Development and validation of a pixel wise deep learning model to detect cataract on swept-source optical coherence tomography images.

Journal of optometry
PURPOSE: The diagnosis of cataract is mostly clinical and there is a lack of objective and specific tool to detect and grade it automatically. The goal of this study was to develop and validate a deep learning model to detect and localize cataract on...

Deep-Learning-Based Fast Optical Coherence Tomography (OCT) Image Denoising for Smart Laser Osteotomy.

IEEE transactions on medical imaging
Laser osteotomy promises precise cutting and minor bone tissue damage. We proposed Optical Coherence Tomography (OCT) to monitor the ablation process toward our smart laser osteotomy approach. The OCT image is helpful to identify tissue type and prov...

Automated Detection of Epiretinal Membranes in OCT Images Using Deep Learning.

Ophthalmic research
INTRODUCTION: Development and validation of a deep learning algorithm to automatically identify and locate epiretinal memberane (ERM) regions in OCT images.

Training Deep Learning Models to Work on Multiple Devices by Cross-Domain Learning with No Additional Annotations.

Ophthalmology
PURPOSE: To create an unsupervised cross-domain segmentation algorithm for segmenting intraretinal fluid and retinal layers on normal and pathologic macular OCT images from different manufacturers and camera devices.

Imaging of the optic nerve: technological advances and future prospects.

The Lancet. Neurology
Over the past decade, ocular imaging strategies have greatly advanced the diagnosis and follow-up of patients with optic neuropathies. Developments in optic nerve imaging have specifically improved the care of patients with papilloedema and idiopathi...