Deep-learning based, automated segmentation of macular edema in optical coherence tomography (original) (raw)

Automatic Segmentation of Retinal Fluid and Photoreceptor Layer from Optical Coherence Tomography Images of Diabetic Macular Edema Patients Using Deep Learning and Associations with Visual Acuity

Yu-te Wu

Biomedicines

View PDFchevron_right

The Classification of Common Macular Diseases Using Deep Learning on Optical Coherence Tomography Images with and without Prior Automated Segmentation

Sukhum Silpa-archa

Diagnostics

View PDFchevron_right

Automated Detection of Macular Diseases by Optical Coherence Tomography and Artificial Intelligence Machine Learning of Optical Coherence Tomography Images

Tsutomu Yasukawa

Journal of Ophthalmology

View PDFchevron_right

Cystoid macular edema segmentation of Optical Coherence Tomography images using fully convolutional neural networks and fully connected CRFs

Stuart Gibson

ArXiv, 2017

View PDFchevron_right

Automatic Classification of Retinal Optical Coherence Tomography Images With Layer Guided Convolutional Neural Network

Leyuan Fang

IEEE Signal Processing Letters, 2019

View PDFchevron_right

Optical Coherence Tomography-Based Deep-Learning Models for Classifying Normal and Age-Related Macular Degeneration and Exudative and Non-Exudative Age-Related Macular Degeneration Changes

Yasuo Kurimoto

Ophthalmology and Therapy, 2019

View PDFchevron_right

Fusing Results of Several Deep Learning Architectures for Automatic Classification of Normal and Diabetic Macular Edema in Optical Coherence Tomography

Genevieve Chan

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2018

View PDFchevron_right

Epiretinal Membrane Detection at the Ophthalmologist Level using Deep Learning of Optical Coherence Tomography

Henry Bair

Scientific Reports

View PDFchevron_right

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

Tấn Hải Phạm

British Journal of Ophthalmology, 2020

View PDFchevron_right

Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach

Masood Naseripour

Scientific Reports

View PDFchevron_right

Deep learning to infer visual acuity from optical coherence tomography in diabetic macular edema

yu-bai Chou

Frontiers in Medicine

View PDFchevron_right

Distinguishing retinal angiomatous proliferation from polypoidal choroidal vasculopathy with a deep neural network based on optical coherence tomography

Jeewoo Yoon

Scientific Reports, 2021

View PDFchevron_right

Deep learning to detect macular atrophy in wet age-related macular degeneration using optical coherence tomography

Francesca Cordeiro

Scientific Reports

View PDFchevron_right

A Deep Ensemble Learning-Based CNN Architecture for Multiclass Retinal Fluid Segmentation in OCT Images

Abhishek Kothari

IEEE Access

View PDFchevron_right

ClaRet -- A CNN Architecture for Optical Coherence Tomography

Adit Magotra

Cornell University - arXiv, 2022

View PDFchevron_right

Automatic quantification of superficial foveal avascular zone in optical coherence tomography angiography implemented with deep learning

Allen Cheong

Visual Computing for Industry, Biomedicine, and Art

View PDFchevron_right

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning

Subhashini Venugopalan

Nature Communications

View PDFchevron_right

Segmentation of Preretinal Space in Optical Coherence Tomography Images Using Deep Neural Networks

Agnieszka A Stankiewicz (Krzykowska)

Sensors

View PDFchevron_right

Hybrid CNN Based Computer-Aided Diagnosis System for Choroidal Neovascularization, Diabetic Macular Edema, Drusen Disease Detection from OCT Images

Ahmet Çinar

Traitement du Signal, 2021

View PDFchevron_right

Multi-Lesion Segmentation of Diabetic Retinopathy Using Deep Learning

IJRASET Publication

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

View PDFchevron_right

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography

sebastian montenegro N20

Computer Methods and Programs in Biomedicine, 2019

View PDFchevron_right

Deep learning-based classification of eye diseases using Convolutional Neural Network for OCT images

Mohamed elkholy, Marwa A. Marzouk

Deep learning-based classification of eye diseases using Convolutional Neural Network for OCT images, 2024

View PDFchevron_right

Classification of Optical Coherence Tomography using Convolutional Neural Networks

Salviano Soares

Bioinformatics, 2020

View PDFchevron_right

Clinically applicable deep learning for diagnosis and referral in retinal disease

Dawn Sim

Nature Medicine, 2018

View PDFchevron_right

Deep Learning-Based Segmentation and Quantification of Retinal Capillary Non-Perfusion on Ultra-Wide-Field Retinal Fluorescein Angiography

rajna rasheed

Journal of Clinical Medicine

View PDFchevron_right

Retinal disease classification based on optical coherence tomography images using convolutional neural networks

Drazen Draskovic

Journal of Electronic Imaging, 2022

View PDFchevron_right

Automatic Detection of AMD and DME Retinal Pathologies Using Deep Learning

Nawres KHLIFA

International Journal of Biomedical Imaging

View PDFchevron_right

Retinal Disease Classification from OCT Images Using Deep Learning Algorithms

Loc Tran

2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2021

View PDFchevron_right

RETOUCH -The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge

Ruwan Tennakoon

IEEE Transactions on Medical Imaging

View PDFchevron_right

Application of deep learning for retinal image analysis: A review

muhammad haris haris

Computer Science Review, 2020

View PDFchevron_right

Automated Segmentation of the Choroid in EDI-OCT Images with Retinal Pathology Using Convolution Neural Networks

jiancong wang

Fetal, Infant and Ophthalmic Medical Image Analysis, 2017

View PDFchevron_right

Detection of retinal diseases from ophthalmological images based on convolutional neural network architecture

sezin barın

Acta Scientiarum. Technology

View PDFchevron_right