DVAE: Deep Variational Auto-Encoders for Denoising Retinal Fundus Image

2019 ◽  
pp. 257-273
Author(s):  
Biswajit Biswas ◽  
Swarup Kr Ghosh ◽  
Anupam Ghosh
Keyword(s):  
Fundus Image ◽  
Retinal Fundus Image ◽  
Retinal Fundus

scholarly journals Image Preprocessing in Classification and Identification of Diabetic Eye Diseases

2021 ◽  
Author(s):  
Rubina Sarki ◽  
Khandakar Ahmed ◽  
Hua Wang ◽  
Yanchun Zhang ◽  
Jiangang Ma ◽  
...  
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Geometric Transformation ◽  
Diabetic Patients ◽  
Fundus Image ◽  
Classification Problems ◽  
Specificity And Sensitivity ◽  
Retinal Fundus Image ◽  
Retinal Fundus ◽  
Traditional Image

AbstractDiabetic eye disease (DED) is a cluster of eye problem that affects diabetic patients. Identifying DED is a crucial activity in retinal fundus images because early diagnosis and treatment can eventually minimize the risk of visual impairment. The retinal fundus image plays a significant role in early DED classification and identification. An accurate diagnostic model’s development using a retinal fundus image depends highly on image quality and quantity. This paper presents a methodical study on the significance of image processing for DED classification. The proposed automated classification framework for DED was achieved in several steps: image quality enhancement, image segmentation (region of interest), image augmentation (geometric transformation), and classification. The optimal results were obtained using traditional image processing methods with a new build convolution neural network (CNN) architecture. The new built CNN combined with the traditional image processing approach presented the best performance with accuracy for DED classification problems. The results of the experiments conducted showed adequate accuracy, specificity, and sensitivity.

Non-Invasive Contrast Normalisation and Denosing Technique for the Retinal Fundus Image

2016 ◽  
Vol 3 (3) ◽  
pp. 265-279 ◽  
Author(s):  
Toufique Ahmed Soomro ◽  
Junbin Gao
Keyword(s):  
Fundus Image ◽  
Non Invasive ◽  
Retinal Fundus Image ◽  
Retinal Fundus

scholarly journals A Simple Method for Optic Disk Segmentation from Retinal Fundus Image

2014 ◽  
Vol 6 (11) ◽  
pp. 36-42 ◽  
Author(s):  
Adithya Kusuma Whardana ◽  
◽  
Nanik Suciati ◽  
Keyword(s):  
Optic Disk ◽  
Fundus Image ◽  
Simple Method ◽  
Retinal Fundus Image ◽  
Retinal Fundus

Feature extraction from retinal fundus image for early detection of diabetic retinopathy

2013 ◽  
Author(s):  
Syna Sreng ◽  
Jun-Ichi Takada ◽  
Noppadol Maneerat ◽  
Don Isarakorn ◽  
Ruttikorn Varakulsiripunth ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Diabetic Retinopathy ◽  
Early Detection ◽  
Fundus Image ◽  
Retinal Fundus Image ◽  
Retinal Fundus

A Review: Hemorrhage Detection Methodologies on the Retinal Fundus Image

2021 ◽  
pp. 365-374
Author(s):  
Niladri Sekhar Datta ◽  
Koushik Majumder ◽  
Amritayan Chatterjee ◽  
Himadri Sekhar Dutta ◽  
Sumana Chatterjee
Keyword(s):  
Fundus Image ◽  
Retinal Fundus Image ◽  
Retinal Fundus
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