AI Medical Compendium Topic:
Tomography, Optical Coherence

Clear Filters Showing 431 to 440 of 764 articles

4D deep learning for real-time volumetric optical coherence elastography.

International journal of computer assisted radiology and surgery
PURPOSE: Elasticity of soft tissue provides valuable information to physicians during treatment and diagnosis of diseases. A number of approaches have been proposed to estimate tissue stiffness from the shear wave velocity. Optical coherence elastogr...

Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images.

The British journal of ophthalmology
BACKGROUND/AIMS: Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosis and treatment of many eye diseases, especially angl...

Combining Deep Learning With Optical Coherence Tomography Imaging to Determine Scalp Hair and Follicle Counts.

Lasers in surgery and medicine
BACKGROUND AND OBJECTIVES: One of the challenges in developing effective hair loss therapies is the lack of reliable methods to monitor treatment response or alopecia progression. In this study, we propose the use of optical coherence tomography (OCT...

Detecting mouse squamous cell carcinoma from submicron full-field optical coherence tomography images by deep learning.

Journal of biophotonics
The standard medical practice for cancer diagnosis requires histopathology, which is an invasive and time-consuming procedure. Optical coherence tomography (OCT) is an alternative that is relatively fast, noninvasive, and able to capture three-dimens...

Detection of Glaucoma Deterioration in the Macular Region with Optical Coherence Tomography: Challenges and Solutions.

American journal of ophthalmology
PURPOSE: Macular imaging with optical coherence tomography (OCT) measures the most critical retinal ganglion cells (RGCs) in the human eye. The goal of this perspective is to review the challenges to detection of glaucoma progression with macular OCT...

Development of Deep Learning Models to Predict Best-Corrected Visual Acuity from Optical Coherence Tomography.

Translational vision science & technology
PURPOSE: To develop deep learning (DL) models to predict best-corrected visual acuity (BCVA) from optical coherence tomography (OCT) images from patients with neovascular age-related macular degeneration (nAMD).

Prediction of visual field from swept-source optical coherence tomography using deep learning algorithms.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To develop a deep learning method to predict visual field (VF) from wide-angle swept-source optical coherence tomography (SS-OCT) and compare the performance of three Google Inception architectures.

Unbiased identification of novel subclinical imaging biomarkers using unsupervised deep learning.

Scientific reports
Artificial intelligence has recently made a disruptive impact in medical imaging by successfully automatizing expert-level diagnostic tasks. However, replicating human-made decisions may inherently be biased by the fallible and dogmatic nature of hum...