Deep Learning for Automated Quality Assessment of Color Fundus Images in Diabetic Retinopathy Screening

03/07/2017
by   Sajib Kumar Saha, et al.
0

Purpose To develop a computer based method for the automated assessment of image quality in the context of diabetic retinopathy (DR) to guide the photographer. Methods A deep learning framework was trained to grade the images automatically. A large representative set of 7000 color fundus images were used for the experiment which were obtained from the EyePACS that were made available by the California Healthcare Foundation. Three retinal image analysis experts were employed to categorize these images into Accept and Reject classes based on the precise definition of image quality in the context of DR. A deep learning framework was trained using 3428 images. Results A total of 3572 images were used for the evaluation of the proposed method. The method shows an accuracy of 100 and Reject images. Conclusion Image quality is an essential prerequisite for the grading of DR. In this paper we have proposed a deep learning based automated image quality assessment method in the context of DR. The method can be easily incorporated with the fundus image capturing system and thus can guide the photographer whether a recapture is necessary or not.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 5

page 11

page 12

page 13

07/10/2019

Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces

Retinal image quality assessment (RIQA) is essential for controlling the...
08/28/2020

Human Blastocyst Classification after In Vitro Fertilization Using Deep Learning

Embryo quality assessment after in vitro fertilization (IVF) is primaril...
05/02/2022

FundusQ-Net: a Regression Quality Assessment Deep Learning Algorithm for Fundus Images Quality Grading

Objective: Ophthalmological pathologies such as glaucoma, diabetic retin...
07/25/2021

Distributional Shifts in Automated Diabetic Retinopathy Screening

Deep learning-based models are developed to automatically detect if a re...
01/26/2021

Evidence Based Prediction and Progression Monitoring on Retinal Images from Three Nations

Purpose: The aim of this work is to demonstrate how a retinal image anal...
12/31/2020

A Deep Retinal Image Quality Assessment Network with Salient Structure Priors

Retinal image quality assessment is an essential prerequisite for diagno...
10/28/2021

Degraded Reference Image Quality Assessment

In practical media distribution systems, visual content usually undergoe...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.