Cargando…

Automated diagnosis of diabetic retinopathy and glaucoma using fundus and OCT images

We describe a system for the automated diagnosis of diabetic retinopathy and glaucoma using fundus and optical coherence tomography (OCT) images. Automatic screening will help the doctors to quickly identify the condition of the patient in a more accurate way. The macular abnormalities caused due to...

Descripción completa

Detalles Bibliográficos
Autores principales:	Pachiyappan, Arulmozhivarman, Das, Undurti N, Murthy, Tatavarti VSP, Tatavarti, Rao
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2012
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3477058/ https://www.ncbi.nlm.nih.gov/pubmed/22695250 http://dx.doi.org/10.1186/1476-511X-11-73

Ejemplares similares

Data on OCT and fundus images for the detection of glaucoma
por: Raja, Hina, et al.
Publicado: (2020)

The many challenges in automated glaucoma diagnosis based on fundus imaging
por: Krishnadas, R
Publicado: (2021)

Effect of an Integrated Naturopathy and Yoga Program on Long-Term Glycemic Control in Type 2 Diabetes Mellitus Patients: A Prospective Cohort Study
por: Bairy, Srinivas, et al.
Publicado: (2020)

Selfie fundus imaging for diabetic retinopathy screening
por: Kumari, Somya, et al.
Publicado: (2021)

Dataset from fundus images for the study of diabetic retinopathy
por: Castillo Benítez, Veronica Elisa, et al.
Publicado: (2021)

Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image
por: Xu, Kele, et al.
Publicado: (2017)

Radiomics-Based Assessment of OCT Angiography Images for Diabetic Retinopathy Diagnosis
por: Carrera-Escalé, Laura, et al.
Publicado: (2022)

Registration of OCT fundus images with color fundus photographs based on blood vessel ridges
por: Li, Ying, et al.
Publicado: (2010)

Machine Learning Based Automated Segmentation and Hybrid Feature Analysis for Diabetic Retinopathy Classification Using Fundus Image
por: Ali, Aqib, et al.
Publicado: (2020)

Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence
por: Rajalakshmi, Ramachandran, et al.
Publicado: (2018)

Semi-automated quantification of hard exudates in colour fundus photographs diagnosed with diabetic retinopathy
por: Marupally, Abhilash Goud, et al.
Publicado: (2017)

Data on fundus images for vessels segmentation, detection of hypertensive retinopathy, diabetic retinopathy and papilledema
por: Akram, Muhammad Usman, et al.
Publicado: (2020)

Automated Detection of Malarial Retinopathy in Digital Fundus Images for Improved Diagnosis in Malawian Children with Clinically Defined Cerebral Malaria
por: Joshi, Vinayak, et al.
Publicado: (2017)

Automated Glaucoma Screening and Diagnosis Based on Retinal Fundus Images Using Deep Learning Approaches: A Comprehensive Review
por: Zedan, Mohammad J. M., et al.
Publicado: (2023)

Diabetic maculopathy: multicolour and SD-OCT versus fundus photography
por: Kousha, Obaid, et al.
Publicado: (2021)

Comparison of Color Fundus Photography and Multicolor Fundus Imaging for Detection of Lesions in Diabetic Retinopathy and Retinal Vein Occlusion
por: Castro, Catarina, et al.
Publicado: (2023)

A generalizable deep learning regression model for automated glaucoma screening from fundus images
por: Hemelings, Ruben, et al.
Publicado: (2023)

Fundus fluorescence Angiography in diagnosing diabetic retinopathy
por: Wang, Shuhui, et al.
Publicado: (2017)

Deep-Learning–Aided Diagnosis of Diabetic Retinopathy, Age-Related Macular Degeneration, and Glaucoma Based on Structural and Angiographic OCT
por: Zang, Pengxiao, et al.
Publicado: (2022)

Effective Fundus Image Decomposition for the Detection of Red Lesions and Hard Exudates to Aid in the Diagnosis of Diabetic Retinopathy
por: Romero-Oraá, Roberto, et al.
Publicado: (2020)

Hybrid Methods for Fundus Image Analysis for Diagnosis of Diabetic Retinopathy Development Stages Based on Fusion Features
por: Alshahrani, Mohammed, et al.
Publicado: (2023)

Validation of Artificial Intelligence Algorithm in the Detection and Staging of Diabetic Retinopathy through Fundus Photography: An Automated Tool for Detection and Grading of Diabetic Retinopathy
por: Pawar, Bhargavi, et al.
Publicado: (2021)

OCT for glaucoma diagnosis, screening and detection of glaucoma progression
por: Bussel, Igor I, et al.
Publicado: (2014)

Differential distribution of manifest lesions in diabetic retinopathy by fundus fluorescein angiography and fundus photography
por: Li, Xiaoli, et al.
Publicado: (2020)

Automatic analysis of selected choroidal diseases in OCT images of the eye fundus
por: Koprowski, Robert, et al.
Publicado: (2013)

Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
por: Sahlsten, Jaakko, et al.
Publicado: (2019)

Digital image processing software for diagnosing diabetic retinopathy from fundus photograph
por: Ratanapakorn, Tanapat, et al.
Publicado: (2019)

An interpretable multiple-instance approach for the detection of referable diabetic retinopathy in fundus images
por: Papadopoulos, Alexandros, et al.
Publicado: (2021)

Automatic Screening of Diabetic Retinopathy Using Fundus Images and Machine Learning Algorithms
por: Mujeeb Rahman, K. K., et al.
Publicado: (2022)

Associated factors of diabetic retinopathy by artificial intelligence evaluation of fundus images in Japan
por: Komatsu, Koji, et al.
Publicado: (2023)

Near-infrared fundus autoflorescence imaging in solar retinopathy
por: Czepita, Maciej, et al.
Publicado: (2017)

Wide-Field Megahertz OCT Imaging of Patients with Diabetic Retinopathy
por: Reznicek, Lukas, et al.
Publicado: (2015)

Diabetic macular edema, retinopathy and age-related macular degeneration as inflammatory conditions
por: Das, Undurti N.
Publicado: (2016)

Community care for diabetic retinopathy and glaucoma in India: A panel discussion
por: Rani, Padmaja Kumari, et al.
Publicado: (2018)

Chákṣu: A glaucoma specific fundus image database
por: Kumar, J. R. Harish, et al.
Publicado: (2023)

Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images
por: An, Guangzhou, et al.
Publicado: (2019)

Automated Diabetic Retinopathy Detection Using Horizontal and Vertical Patch Division-Based Pre-Trained DenseNET with Digital Fundus Images
por: Kobat, Sabiha Gungor, et al.
Publicado: (2022)

Analysis of retinal nerve fiber layer birefringence in patients with glaucoma and diabetic retinopathy by polarization sensitive OCT
por: Desissaire, Sylvia, et al.
Publicado: (2020)

Automated diagnosing primary open-angle glaucoma from fundus image by simulating human’s grading with deep learning
por: Lin, Mingquan, et al.
Publicado: (2022)

Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach
por: Somasundaram, K., et al.
Publicado: (2015)

Cannot write session to /tmp/vufind_sessions/sess_nrkj8790h3d0buh87gnakmjb6v