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 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.

An Approach for Automatic Detection and Grading of Macular Edema

2015 ◽  
pp. 204-231
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 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

scholarly journals Modified Curvature-based Trigonometric Identities for Retinal Blood Vessel Tortuosity Measurement in Diabetic Retinopathy Fundus Images

2018 ◽  
Vol 7 (4.11) ◽  
pp. 133
Author(s):  
N. Badariah A. Mustafa ◽  
W. Mimi Diyana W. Zaki ◽  
Aini Hussain ◽  
Jemaima Che Hamzah
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessel ◽  
False Negative ◽  
False Negative Rate ◽  
Fundus Images ◽  
Current Clinical Practice ◽  
Clinical Experiences ◽  
Retinal Blood Vessel ◽  
Specific Standard ◽  
Vessel Curvature

In current clinical practice, there is no specific standard and grading system that can be used to measure the behaviour of the retinal blood vessel curvature. The retinal blood vessel curvature is measured based on clinical experiences. It is very subjective and inconsistent to describe the presence of tortuosity in fundus images. Thus, this paper aims to measure the tortuosity of retinal blood vessel using curvature-based method and investigate its relationship with diabetic retinopathy (DR) disease. The proposed tortuosity measures have been tested on 43 fundus images belonging to patients who have been diagnosed with DR disease and validated by two clinical experts from our collaborative hospital. On average, the proposed algorithm achieved 90.7% (accuracy), 98.72% (sensitivity) and 9.3% (false negative rate), that shows significant tortuosity presence in diabetic retinopathy fundus images. 

Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Fuzzy Image Processing

2015 ◽  
pp. 379-388 ◽  
Author(s):  
Sarni Suhaila Rahim ◽  
Vasile Palade ◽  
Chrisina Jayne ◽  
Andreas Holzinger ◽  
James Shuttleworth
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Fundus Images ◽  
Fuzzy Image

A method to assist in the diagnosis of early diabetic retinopathy: Image processing applied to detection of microaneurysms in fundus images

2015 ◽  
Vol 44 ◽  
pp. 41-53 ◽  
Author(s):  
Roberto Rosas-Romero ◽  
Jorge Martínez-Carballido ◽  
Jonathan Hernández-Capistrán ◽  
Laura J. Uribe-Valencia
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
Fundus Images
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