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. 

scholarly journals Retinal Blood Vessel and Optic Disc Segmentation

2019 ◽  
Vol 8 (2) ◽  
pp. 833-838
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessel ◽  
Optic Disc ◽  
Diabetic Patients ◽  
Retinal Vessels ◽  
Retinal Blood Vessel ◽  
Computerized Screening ◽  
Retinal Fundus

Diabetic Retinopathy (DR) is a main source of vision misfortune in diabetic patients. DR is a predominantly caused because of the harm caused in retinal veins of a diabetic patients. It is fundamental to recognize and fragment their tinal veins for DR identification and determination, which avoids prior vision misfortune in diabetic patients. The PC helped programmed discovery and division of veins through the end of optic location district in Retina. Optic Disc (OD) discovery is a principle step while creating computerized screening framework for diabetic retinopathy. This is a technique to naturally recognize the situation of the OD in advanced retinal fundus pictures. The strategy begins by normalizing glow and difference all through the picture utilizing brightening evening out and versatile histogram balance techniques individually. The OD recognition calculation depends on coordinating the normal directional example of the retinal veins. Henceforth, a straightforward coordinated channel is proposed to generally coordinate the headings of the vessels at the OD region. The retinal vessels are portioned utilizing a basic and standard 2-D Gaussian coordinated channel.

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.

Flexible architectures for retinal blood vessel segmentation in high-resolution fundus images

2016 ◽  
Vol 15 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Hamza Bendaoudi ◽  
Farida Cheriet ◽  
Ashley Manraj ◽  
Houssem Ben Tahar ◽  
J. M. Pierre Langlois
Keyword(s):  
High Resolution ◽  
Blood Vessel ◽  
Vessel Segmentation ◽  
Fundus Images ◽  
Retinal Blood Vessel ◽  
Blood Vessel Segmentation ◽  
Flexible Architectures

scholarly journals Automated Detection of Microaneurysmsusing Probabilistic Cascaded Neural Network

2018 ◽  
Vol 11 (3) ◽  
pp. 1083
Author(s):  
Jeyapriya J ◽  
K S Umadevi ◽  
R Jagadeesh Kannan
Keyword(s):  
Neural Network ◽  
Diabetic Retinopathy ◽  
Blood Vessel ◽  
Automated Detection ◽  
Convolution Neural Network ◽  
Retinal Images ◽  
Fundus Images ◽  
Catching Up

The diagnosing features for Diabetic Retinopathy (DR) comprises of features occurring in and around the regions of blood vessel zone which will result into exudes, hemorrhages, microaneurysms and generation of textures on the albumen region of eye balls. In this study we presenta probabilistic convolution neural network based algorithms, utilized for the extraction of such features from the retinal images of patient’s eyeballs. The classifications proficiency of various DR systems is tabulated and examined. The majority of the reported systems are profoundly advanced regarding the analyzed fundus images is catching up to the human ophthalmologist’s characterization capacities.

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