scholarly journals Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
D. Siva Sundhara Raja ◽  
S. Vasuki
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
Anisotropic Diffusion ◽  
Vision Loss ◽  
Automatic Detection ◽  
Diabetic Patients ◽  
Morphological Operations ◽  
Anisotropic Diffusion Filter ◽  
Retinal Blood Vessels ◽  
Detection And Diagnosis

Diabetic retinopathy (DR) is a leading cause of vision loss in diabetic patients. DR is mainly caused due to the damage of retinal blood vessels in the diabetic patients. It is essential to detect and segment the retinal blood vessels for DR detection and diagnosis, which prevents earlier vision loss in diabetic patients. The computer aided automatic detection and segmentation of blood vessels through the elimination of optic disc (OD) region in retina are proposed in this paper. The OD region is segmented using anisotropic diffusion filter and subsequentially the retinal blood vessels are detected using mathematical binary morphological operations. The proposed methodology is tested on two different publicly available datasets and achieved 93.99% sensitivity, 98.37% specificity, 98.08% accuracy in DRIVE dataset and 93.6% sensitivity, 98.96% specificity, and 95.94% accuracy in STARE dataset, respectively.

scholarly journals Diabetic Exudate Detection in Color Retinal Images

2019 ◽  
Vol 19 ◽  
pp. 7510-7518
Author(s):  
Dalia Ali
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
High Performance ◽  
Vision Loss ◽  
Vascular Complication ◽  
Processing Method ◽  
Retinal Images ◽  
Morphological Operations ◽  
Positive Predicted Value

Diabetic retinopathy is a vascular complication of long-term diabetes. It causes damage to the small blood vessels positioned in the retina. These damaged blood vessels affect the macula and lead to vision loss. Exudates are one of the early signs of diabetic retinopathy disease in the retinal image, which occurs due to built-up of lipidic accumulation within the retina. In this paper, an image processing method is presented for diabetic exudates detection. First, high performance pre-processing is applied not only for de-noising and normalization but also to remove artefacts and reflection that could mislead exudates detection. Then, morphological operations are applied for the final candidate segmentation. Eight region features are extracted from the exudate region then random forest classifier is applied to differentiate between exudates and non-exudates region. The proposed method is evaluated using e_ophtha_EX dataset, achieving 80% sensitivity and 77% positive predicted value.

scholarly journals Identification of Hemorrhages in Iris Using Hybrid Morphological Method

2020 ◽  
Vol 8 (3) ◽  
pp. 01-05
Author(s):  
Robbi Rahim
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessel ◽  
Blood Vessels ◽  
Diabetic Patients ◽  
Morphological Operations ◽  
Critical Factors ◽  
Image Subtraction ◽  
The Past ◽  
Image Thinning

In the field of ophthalmology, hemorrhage is the term used more often because of increasing diabetic patients. It’s a challenge amidst the ophthalmologist to distinguish the hemorrhage from the blood vessels, these lands in various problems. In the past various techniques were employed for the detection of the hemorrhage but they were not so accurate and often encountered misclassification between hemorrhage and blood vessels. Precise detection and classification of hemorrhage and blood vessel is very important in the diagnosis of many problems. This paper depicts a mechanized procedure for recognizing hemorrhages in fundus pictures. The acknowledgment of hemorrhages is one of the critical factors in the early finish of diabetic retinopathy. The algorithm proceeds through several steps such as image enhancement, image subtraction, morphological operations such as image thresholding, image strengthening, image thinning, erosion, morphological closing, image complement to suppress blood vessels and to highlight the hemorrhages

scholarly journals Blood Vessels Detection of Diabetic Retinopathy from Retinal Fundus Image using Image Processing Techniques

2020 ◽  
Vol 18 (44) ◽  
pp. 1-16
Author(s):  
Faleh H. Mahmood
Keyword(s):  
Diabetic Retinopathy ◽  
Early Detection ◽  
Blood Vessel ◽  
Blood Vessels ◽  
Vision Loss ◽  
Digital Camera ◽  
Eye Diseases ◽  
Morphological Operations ◽  
Structuring Element ◽  
Processing Techniques

 abstract Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from the digital fundus images. In this research, a novel methodology was introduced to separate retinal blood vessel network. The suggested system in this research involves four stages, after image acquisition, the pre-processes of the image to preparing and improving the image quality is the first stage. Morphological operations are used for the detection of blood vessels. In this research, we will use two morphological operations: erosion and dilation. These two operations have two inputs, a binary image, and a structuring element object. We will use two morphological processes (boundary extraction and top, bottom hat transform). Before these operations, we will use applying a canny edge detector technique to obtain the edges of the retina image. The technique is tried on shading retinal pictures acquired from STARE and DRIVE databases which are accessible on the web as well as the samples of retinal images were obtained from the digital camera from Ibn Al-Haytham specialist Hospital for Eye in Baghdad, Iraq. Good results and effective were obtained for blood vessel detected and extract  

Review of Various Tasks Performed in the Preprocessing Phase of a Diabetic Retinopathy Diagnosis System

2020 ◽  
Vol 16 (4) ◽  
pp. 397-426
Author(s):  
Muhammad Nadeem Ashraf ◽  
Muhammad Hussain ◽  
Zulfiqar Habib
Keyword(s):  
Diabetic Retinopathy ◽  
Blood Vessels ◽  
Early Stage ◽  
Spherical Shape ◽  
Cost Effective ◽  
Lesion Detection ◽  
Diabetic Patients ◽  
Cad System ◽  
Non Invasive ◽  
Optic Discs

Diabetic Retinopathy (DR) is a major cause of blindness in diabetic patients. The increasing population of diabetic patients and difficulty to diagnose it at an early stage are limiting the screening capabilities of manual diagnosis by ophthalmologists. Color fundus images are widely used to detect DR lesions due to their comfortable, cost-effective and non-invasive acquisition procedure. Computer Aided Diagnosis (CAD) of DR based on these images can assist ophthalmologists and help in saving many sight years of diabetic patients. In a CAD system, preprocessing is a crucial phase, which significantly affects its performance. Commonly used preprocessing operations are the enhancement of poor contrast, balancing the illumination imbalance due to the spherical shape of a retina, noise reduction, image resizing to support multi-resolution, color normalization, extraction of a field of view (FOV), etc. Also, the presence of blood vessels and optic discs makes the lesion detection more challenging because these two artifacts exhibit specific attributes, which are similar to those of DR lesions. Preprocessing operations can be broadly divided into three categories: 1) fixing the native defects, 2) segmentation of blood vessels, and 3) localization and segmentation of optic discs. This paper presents a review of the state-of-the-art preprocessing techniques related to three categories of operations, highlighting their significant aspects and limitations. The survey is concluded with the most effective preprocessing methods, which have been shown to improve the accuracy and efficiency of the CAD systems.

scholarly journals Plasma microRNA signature associated with retinopathy in patients with type 2 diabetes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Donato Santovito ◽  
Lisa Toto ◽  
Velia De Nardis ◽  
Pamela Marcantonio ◽  
Rossella D’Aloisio ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Vision Loss ◽  
External Validation ◽  
Diabetic Patients ◽  
Disease Biomarkers ◽  
Response To Stress ◽  
Severity Of The Disease ◽  
Plasma Microrna

AbstractDiabetic retinopathy (DR) is a leading cause of vision loss and disability. Effective management of DR depends on prompt treatment and would benefit from biomarkers for screening and pre-symptomatic detection of retinopathy in diabetic patients. MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression which are released in the bloodstream and may serve as biomarkers. Little is known on circulating miRNAs in patients with type 2 diabetes (T2DM) and DR. Here we show that DR is associated with higher circulating miR-25-3p (P = 0.004) and miR-320b (P = 0.011) and lower levels of miR-495-3p (P < 0.001) in a cohort of patients with T2DM with DR (n = 20), compared with diabetic subjects without DR (n = 10) and healthy individuals (n = 10). These associations persisted significant after adjustment for age, gender, and HbA1c. The circulating levels of these miRNAs correlated with severity of the disease and their concomitant evaluation showed high accuracy for identifying DR (AUROC = 0.93; P < 0.001). Gene ontology analysis of validated targets revealed enrichment in pathways such as regulation of metabolic process (P = 1.5 × 10–20), of cell response to stress (P = 1.9 × 10–14), and development of blood vessels (P = 2.7 × 10–14). Pending external validation, we anticipate that these miRNAs may serve as putative disease biomarkers and highlight novel molecular targets for improving care of patients with diabetic retinopathy.

scholarly journals Utilization of diabetic retinopathy screening among diabetic patients at a tertiary care hospital in Kerala, India

2021 ◽  
Vol 8 (10) ◽  
pp. 4938
Author(s):  
Sona Sabitha Kumar ◽  
Lathika Vasu Kamaladevi ◽  
Sruthi Mankara Valsan
Keyword(s):  
Diabetic Retinopathy ◽  
Vision Loss ◽  
Adult Population ◽  
Tertiary Care ◽  
Health Concern ◽  
Diabetic Patients ◽  
Care Hospital ◽  
Screening Programs ◽  
Diabetic Retinopathy Screening ◽  
Retinopathy Screening

Background: Diabetes is a major public health concern that affects nearly 463 million (9.3%) of global adult population. Diabetic retinopathy, which affects around 35% of all diabetic patients, is the fifth leading cause of preventable global blindness. This study was done to determine the status of diabetic retinopathy screening and the factors that influence its uptake among diabetic patients attending a tertiary care setting in Kerala, India.Methods: 200 patients with diabetes mellitus on physician care were enrolled for a questionnaire-based survey which collected information on patient demographics, education, occupation, patient’s awareness of retinopathy, screening, diabetic blindness and their source of such knowledge.Results: 83% were aware that diabetes can result in vision loss. 61% were aware that diabetic blindness is preventable. 42% patients were aware of screening options for retinopathy. The awareness of retinopathy screening was significantly associated (p=0.0001) only with duration of diabetes.Conclusions: Awareness of diabetic retinopathy among diabetic patients in Kerala was sub optimal. Better patient education and use of mass media can increase awareness on diabetes retinopathy screening programs. 

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