AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Tomography, Optical Coherence

Showing 241 to 250 of 762 articles

Clear Filters

Deep learning-based 3D OCT imaging for detection of lamina cribrosa defects in eyes with high myopia.

Scientific reports
The lamina cribrosa (LC) is a collagenous tissue located in the optic nerve head, and its dissection is observed in eyes with pathologic myopia as a LC defect (LCD). The diagnosis of LCD has been difficult because the LC is located deep beneath the r...

KFWC: A Knowledge-Driven Deep Learning Model for Fine-grained Classification of Wet-AMD.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automated diagnosis using deep neural networks can help ophthalmologists detect the blinding eye disease wet Age-related Macular Degeneration (AMD). Wet-AMD has two similar subtypes, Neovascular AMD and Polypoidal Choroidal...

Robot-assisted subretinal injection system: development and preliminary verification.

BMC ophthalmology
BACKGROUND: To design and develop a surgical robot capable of assisting subretinal injection.

Deep learning approaches to predict 10-2 visual field from wide-field swept-source optical coherence tomography en face images in glaucoma.

Scientific reports
Close monitoring of central visual field (VF) defects with 10-2 VF helps prevent blindness in glaucoma. We aimed to develop a deep learning model to predict 10-2 VF from wide-field swept-source optical coherence tomography (SS-OCT) images. Macular ga...

Patch-based CNN for corneal segmentation of AS-OCT images: Effect of the number of classes and image quality upon performance.

Computers in biology and medicine
Anterior segment optical coherence tomography (AS-OCT) is a fundamental ophthalmic imaging technique. AS-OCT images can be examined by experts and segmented to provide quantitative metrics that inform clinical decision making. Manual segmentation of ...

Generative adversarial network-based deep learning approach in classification of retinal conditions with optical coherence tomography images.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To determine whether a deep learning approach using generative adversarial networks (GANs) is beneficial for the classification of retinal conditions with Optical coherence tomography (OCT) images.

Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.

IEEE transactions on bio-medical engineering
Coronary artery disease (CAD) is a cardiovascular condition with high morbidity and mortality. Intravascular optical coherence tomography (IVOCT) has been considered as an optimal imagining system for the diagnosis and treatment of CAD. Constrained b...

Deep Learning-Assisted Detection of Glaucoma Progression in Spectral-Domain OCT.

Ophthalmology. Glaucoma
PURPOSE: To develop and validate a deep learning (DL) model for detection of glaucoma progression using spectral-domain (SD)-OCT measurements of retinal nerve fiber layer (RNFL) thickness.

Diseased thyroid tissue classification in OCT images using deep learning: Towards surgical decision support.

Journal of biophotonics
Intraoperative guidance tools for thyroid surgery based on optical coherence tomography (OCT) could aid distinguish between normal and diseased tissue. However, OCT images are difficult to interpret, thus, real-time automatic analysis could support t...

Utilizing deep learning for dermal matrix quality assessment on in vivo line-field confocal optical coherence tomography images.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Line-field confocal optical coherence tomography (LC-OCT) is an imaging technique providing non-invasive "optical biopsies" with an isotropic spatial resolution of ∼1  μm and deep penetration until the dermis. Analysis of obtained images ...