scholarly journals Automatic detection of diabetic retinopathy and its progression in sequential fundus images of patients with diabetes

2018 ◽  
Vol 97 (4) ◽  
pp. e667-e669
Author(s):  
Alexander Dietzel ◽  
Carolin Schanner ◽  
Aura Falck ◽  
Nina Hautala
Keyword(s):  
Diabetic Retinopathy ◽  
Automatic Detection ◽  
Fundus Images ◽  
Patients With Diabetes

An Approach for Automatic Detection and Grading of Macular Edema

2017 ◽  
pp. 1677-1702
Author(s):  
Jyoti Prakash Medhi
Keyword(s):  
Image Processing ◽  
Decision Making ◽  
Diabetic Retinopathy ◽  
Blood Vessel ◽  
Macular Edema ◽  
Automatic Detection ◽  
Automatic Analysis ◽  
Fundus Images

Prolonged Diabetes causes massive destruction to the retina, known as Diabetic Retinopathy (DR) leading to blindness. The blindness due to DR may consequence from several factors such as Blood vessel (BV) leakage, new BV formation on retina. The effects become more threatening when abnormalities involves the macular region. Here automatic analysis of fundus images becomes important. This system checks for any abnormality and help ophthalmologists in decision making and to analyze more number of cases. The main objective of this chapter is to explore image processing tools for automatic detection and grading macular edema in fundus images.

scholarly journals Evaluation of a System for Automatic Detection of Diabetic Retinopathy From Color Fundus Photographs in a Large Population of Patients With Diabetes

Diabetes Care ◽  
2007 ◽  
Vol 31 (2) ◽  
pp. 193-198 ◽  
Author(s):  
M. D. Abramoff ◽  
M. Niemeijer ◽  
M. S.A. Suttorp-Schulten ◽  
M. A. Viergever ◽  
S. R. Russell ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Large Population ◽  
Automatic Detection ◽  
Patients With Diabetes ◽  
Fundus Photographs

scholarly journals Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening

2015 ◽  
Vol 27 (5) ◽  
pp. 1149-1164 ◽  
Author(s):  
Sarni Suhaila Rahim ◽  
Chrisina Jayne ◽  
Vasile Palade ◽  
James Shuttleworth
Keyword(s):  
Diabetic Retinopathy ◽  
Automatic Detection ◽  
Fundus Images ◽  
Diabetic Retinopathy Screening ◽  
Retinopathy Screening

scholarly journals Automatic detection and classification of diabetic retinopathy from retinal fundus images

2021 ◽  
Author(s):  
Abdullah Biran
Keyword(s):  
Diabetic Retinopathy ◽  
Gabor Filter ◽  
Automatic Detection ◽  
Histogram Equalization ◽  
Support Vector ◽  
Svm Classifier ◽  
Fundus Images ◽  
Retinal Fundus Images ◽  
Retinal Fundus

Automatic Detection and Classification of Diabetic Retinopathy from Retinal Fundus Images by Abdullah Biran, Master of Applied Science, lectrical and computer engineering Department, Ryerson University, 2017. Diabetic Retinopathy (DR) is an eye disease that leads to blindness when it progresses to proliferative level. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness. In this thesis, an automatic algorithm for detecting diabetic retinopathy is presented. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. In addition, Support Vector Machine (SVM) classifier is used to classify retinal images into normal or abnormal cases of DR including non-proliferative (NPDR) or proliferative diabetic retinopathy (PDR). The proposed method has been tested on fundus images from Standard Diabetic Retinopathy Database (DIARETDB). The implementation of the presented methodology was done in MATLAB. The methodology is tested for sensitivity and accuracy.

scholarly journals An Approach for Automatic Detection and Grading of Macular Edema

Ophthalmology ◽  
2018 ◽  
pp. 241-266
Author(s):  
Jyoti Prakash Medhi
Keyword(s):  
Image Processing ◽  
Decision Making ◽  
Diabetic Retinopathy ◽  
Blood Vessel ◽  
Macular Edema ◽  
Automatic Detection ◽  
Automatic Analysis ◽  
Fundus Images

Prolonged Diabetes causes massive destruction to the retina, known as Diabetic Retinopathy (DR) leading to blindness. The blindness due to DR may consequence from several factors such as Blood vessel (BV) leakage, new BV formation on retina. The effects become more threatening when abnormalities involves the macular region. Here automatic analysis of fundus images becomes important. This system checks for any abnormality and help ophthalmologists in decision making and to analyze more number of cases. The main objective of this chapter is to explore image processing tools for automatic detection and grading macular edema in fundus images.

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