AIMC Topic: Tomography, Optical Coherence
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Proof-of-Concept Analysis of a Deep Learning Model to Conduct Automated Segmentation of OCT Images for Macular Hole Volume.
Ophthalmic surgery, lasers & imaging retina
Apr 1, 2022
BACKGROUND AND OBJECTIVE: To determine whether an automated artificial intelligence (AI) model could assess macular hole (MH) volume on swept-source optical coherence tomography (OCT) images.
Automatic segmentation of intraocular lens, the retrolental space and Berger's space using deep learning.
Acta ophthalmologica
Mar 28, 2022
PURPOSE: To develop and validate a deep learning model to automatically segment three structures using an anterior segment optical coherence tomography (AS-OCT): The intraocular lens (IOL), the retrolental space (IOL to the posterior lens capsule) an...
Rethinking the neighborhood information for deep learning-based optical coherence tomography angiography.
Medical physics
Mar 28, 2022
PURPOSE: Optical coherence tomography angiography (OCTA) is a premium imaging modality for noninvasive microvasculature studies. Deep learning networks have achieved promising results in the OCTA reconstruction task, benefiting from their powerful mo...
Development and quantitative assessment of deep learning-based image enhancement for optical coherence tomography.
BMC ophthalmology
Mar 26, 2022
PURPOSE: To develop a deep learning-based framework to improve the image quality of optical coherence tomography (OCT) and evaluate its image enhancement effect with the traditional image averaging method from a clinical perspective.
Automated diagnosis of age-related macular degeneration using multi-modal vertical plane feature fusion via deep learning.
Medical physics
Mar 11, 2022
PURPOSE: To develop a computer-aided diagnostic (CADx) system of age-related macular degeneration (AMD) through feature fusion between infrared reflectance (IR) and optical coherence tomography (OCT) modalities in order to explore the superiority of ...
Deep learning-based simultaneous registration and unsupervised non-correspondence segmentation of medical images with pathologies.
International journal of computer assisted radiology and surgery
Mar 3, 2022
PURPOSE: The registration of medical images often suffers from missing correspondences due to inter-patient variations, pathologies and their progression leading to implausible deformations that cause misregistrations and might eliminate valuable inf...
Deep learning identify retinal nerve fibre and choroid layers as markers of age-related macular degeneration in the classification of macular spectral-domain optical coherence tomography volumes.
Acta ophthalmologica
Mar 1, 2022
Human colorectal cancer tissue assessment using optical coherence tomography catheter and deep learning.
Journal of biophotonics
Feb 28, 2022
Optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering a new mechanism of endoscopic tissue assessment and biopsy targeting, with a high optical resolution and an imaging depth of ~1 mm. Recent...
Application of Improved U-Net Convolutional Neural Network for Automatic Quantification of the Foveal Avascular Zone in Diabetic Macular Ischemia.
Journal of diabetes research
Feb 26, 2022
OBJECTIVES: The foveal avascular zone (FAZ) is a biomarker for quantifying diabetic macular ischemia (DMI), to automate the identification and quantification of the FAZ in DMI, using an improved U-Net convolutional neural network (CNN) and to establi...
Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and OCT Imaging.
Ophthalmology
Feb 21, 2022
PURPOSE: To develop and validate a deep learning (DL) system for predicting each point on visual fields (VFs) from disc and OCT imaging and derive a structure-function mapping.
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