Cargando…

Development of a Fundus Image-Based Deep Learning Diagnostic Tool for Various Retinal Diseases

Artificial intelligence (AI)-based diagnostic tools have been accepted in ophthalmology. The use of retinal images, such as fundus photographs, is a promising approach for the development of AI-based diagnostic platforms. Retinal pathologies usually occur in a broad spectrum of eye diseases, includi...

Descripción completa

Detalles Bibliográficos
Autores principales:	Kim, Kyoung Min, Heo, Tae-Young, Kim, Aesul, Kim, Joohee, Han, Kyu Jin, Yun, Jaesuk, Min, Jung Kee
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142986/ https://www.ncbi.nlm.nih.gov/pubmed/33918998 http://dx.doi.org/10.3390/jpm11050321

Ejemplares similares

Development of a Deep-Learning-Based Artificial Intelligence Tool for Differential Diagnosis between Dry and Neovascular Age-Related Macular Degeneration
por: Heo, Tae-Young, et al.
Publicado: (2020)

A deep learning-based framework for retinal fundus image enhancement
por: Lee, Kang Geon, et al.
Publicado: (2023)

Predicting High Coronary Artery Calcium Score From Retinal Fundus Images With Deep Learning Algorithms
por: Son, Jaemin, et al.
Publicado: (2020)

An interpretable and interactive deep learning algorithm for a clinically applicable retinal fundus diagnosis system by modelling finding-disease relationship
por: Son, Jaemin, et al.
Publicado: (2023)

Simple Code Implementation for Deep Learning–Based Segmentation to Evaluate Central Serous Chorioretinopathy in Fundus Photography
por: Yoo, Tae Keun, et al.
Publicado: (2022)

Effects of Hypertension, Diabetes, and Smoking on Age and Sex Prediction from Retinal Fundus Images
por: Kim, Yong Dae, et al.
Publicado: (2020)

Deep Learning-Based Classification of Inherited Retinal Diseases Using Fundus Autofluorescence
por: Miere, Alexandra, et al.
Publicado: (2020)

Predicting sex from retinal fundus photographs using automated deep learning
por: Korot, Edward, et al.
Publicado: (2021)

Clinical Results of Various Treatments for Retinal Capillary Hemangioma
por: Won, Yeo-Kyoung, et al.
Publicado: (2020)

Automatic Detection of Diabetic Retinopathy in Retinal Fundus Photographs Based on Deep Learning Algorithm
por: Li, Feng, et al.
Publicado: (2019)

Automatic Method for Optic Disc Segmentation Using Deep Learning on Retinal Fundus Images
por: Septiarini, Anindita, et al.
Publicado: (2023)

Prediction of visual impairment in retinitis pigmentosa using deep learning and multimodal fundus images
por: Liu, Tin Yan Alvin, et al.
Publicado: (2023)

Early detection of diabetic retinopathy based on deep learning and ultra-wide-field fundus images
por: Oh, Kangrok, et al.
Publicado: (2021)

Development of deep learning-based detecting systems for pathologic myopia using retinal fundus images
por: Lu, Li, et al.
Publicado: (2021)

Deep Learning-Based Glaucoma Screening Using Regional RNFL Thickness in Fundus Photography
por: Yang, Hyunmo, et al.
Publicado: (2022)

Development and Evaluation of a Deep Learning System for Screening Retinal Hemorrhage Based on Ultra-Widefield Fundus Images
por: Li, Zhongwen, et al.
Publicado: (2020)

Fundus autofluorescence applications in retinal imaging
por: Gabai, Andrea, et al.
Publicado: (2015)

Fundus autofluorescence of retinal angiomatous proliferation
por: Saito, Masaaki, et al.
Publicado: (2020)

Deep learning for detecting retinal detachment and discerning macular status using ultra-widefield fundus images
por: Li, Zhongwen, et al.
Publicado: (2020)

Deep learning-based classification of retinal vascular diseases using ultra-widefield colour fundus photographs
por: Abitbol, Elie, et al.
Publicado: (2022)

Intelligent Diagnosis of Multiple Peripheral Retinal Lesions in Ultra-widefield Fundus Images Based on Deep Learning
por: Wang, Tong, et al.
Publicado: (2023)

Autonomous assessment of spontaneous retinal venous pulsations in fundus videos using a deep learning framework
por: Panahi, Amirhossein, et al.
Publicado: (2023)

A Novel Fundus Image Reading Tool for Efficient Generation of a Multi-dimensional Categorical Image Database for Machine Learning Algorithm Training
por: Park, Sang Jun, et al.
Publicado: (2018)

Deep Learner System Based on Focal Color Retinal Fundus Images to Assist in Diagnosis
por: Zou, Yanli, et al.
Publicado: (2023)

A deep learning model for generating fundus autofluorescence images from color fundus photography
por: Song, Fan, et al.
Publicado: (2023)

Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks
por: Cen, Ling-Ping, et al.
Publicado: (2021)

Learned optical flow for intra-operative tracking of the retinal fundus
por: Ravasio, Claudio S., et al.
Publicado: (2020)

Review of Machine Learning Applications Using Retinal Fundus Images
por: Jeong, Yeonwoo, et al.
Publicado: (2022)

Assessment of the predictive potential of cognitive scores from retinal images and retinal fundus metadata via deep learning using the CLSA database
por: Corbin, Denis, et al.
Publicado: (2022)

Retinal Fundus Image Registration via Vascular Structure Graph Matching
por: Deng, Kexin, et al.
Publicado: (2010)

Retinal Fundus Image Enhancement Using the Normalized Convolution and Noise Removing
por: Dai, Peishan, et al.
Publicado: (2016)

Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning
por: Bajwa, Muhammad Naseer, et al.
Publicado: (2019)

Estimation of Visual Function Using Deep Learning From Ultra-Widefield Fundus Images of Eyes With Retinitis Pigmentosa
por: Nagasato, Daisuke, et al.
Publicado: (2023)

Non-invasive and accurate risk evaluation of cerebrovascular disease using retinal fundus photo based on deep learning
por: An, Lin, et al.
Publicado: (2023)

Clinical applications of fundus autofluorescence in retinal disease
por: Yung, Madeline, et al.
Publicado: (2016)

Quantifying Fundus Autofluorescence in Patients With Retinitis Pigmentosa
por: Schuerch, Kaspar, et al.
Publicado: (2017)

A deep learning model for the detection of both advanced and early glaucoma using fundus photography
por: Ahn, Jin Mo, et al.
Publicado: (2018)

Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography
por: Oh, Richul, et al.
Publicado: (2023)

A deep learning-based diagnostic tool for identifying various diseases via facial images
por: Attallah, Omneya
Publicado: (2022)

Prediction of White Matter Hyperintensity in Brain MRI Using Fundus Photographs via Deep Learning
por: Cho, Bum-Joo, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_crn07hcvpk7evd2ufds1n02epp