Automatic Retinal Image Analysis for the Detection of Diabetic Retinopathy

Automatic Retinal Image Analysis for the Detection of Diabetic Retinopathy

Prasanna Porwal (Shri Guru Gobind Singhji Institute of Engineering and Technology, India), Samiksha Pachade (Shri Guru Gobind Singhji Institute of Engineering and Technology, India), Manesh Kokare (Shri Guru Gobind Singhji Institute of Engineering and Technology, India), Girish Deshmukh (Dr. G. A. Deshmukh Eye Clinic, India) and Vivek Sahasrabuddhe (Shankarrao Chavan Government Medical College, India)
Copyright: © 2018 |Pages: 16
DOI: 10.4018/978-1-5225-2829-6.ch008
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Abstract

Diabetic Retinopathy, a condition in the person affected by diabetes, is most common cause of blindness in the world. Recent research has given a better understanding of requirement in clinical eye care practice to identify better and cheaper ways of identification, management, diagnosis and treatment of retinal disease. The importance of diabetic retinopathy screening programs and difficulty in achieving reliable early diagnosis of diabetic retinopathy at a reasonable cost needs attention to develop computer-aided diagnosis tool. Computer aided disease diagnosis in retinal image analysis could ease mass screening of population with diabetes mellitus and help clinicians in utilizing their time more efficiently. The recent technological advances in computing power, communication systems, and machine learning techniques provide opportunities to the biomedical engineers and computer scientists to meet the requirements of clinical practice. With proper self-care, management, and medical professional support, individuals with diabetes can live a healthy and long life.
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Introduction

Diabetes Mellitus is a metabolic disorder, characterized by hyperglycemia in which there is an excess of glucose circulating in the blood. It is also commonly known as diabetes. Insulin is the hormone secreted by pancreas responsible for maintaining blood glucose level in the body. The pancreas of the person affected with diabetes either cannot produce enough insulin, utilizes it incorrectly or both. Insulin helps the body to utilize glucose from carbohydrates in the food and facilitates it to enter into body cells for getting burned to attain energy. The body normally regulates blood glucose delicately in the fasting state in a range around 4 to 5.5 mmol/L in the plasma. Insulin helps in preventing blood glucose level from getting too high (hyperglycemia) or too low (hypoglycemia).

Hyperglycemia leads to excessive glycosylation of proteins, and this is the primary attribute of the long-term complications of diabetes. Diabetes is usually divided into two categories i.e. ‘Type – I diabetes’ and ‘Type – II diabetes’. Type – I diabetes is characterized by the inadequacy of insulin and Type – II diabetes has attributes showing the pertinent inadequacy of insulin corresponding to insulin resistance. Insulin insufficiency – either complete or partial – is the fundamental component behind diabetes. However, different variables have an impact and can be more critical while considering treatment.

Insulin requirement depends upon a complex balance between various hormones, existing energy stores, physical activity, and resistance to insulin action in muscle, liver and adipose tissue (Worsley & Simmons, 2010). Modern lifestyle in the developing world has significantly reduced physical activity, and people tend to have an intake of high-calorie food which results in an imbalance of energy that further leads to greater obesity, insulin resistance, and Type – II diabetes. Insulin resistance is defined as the downgraded capacity of peripheral tissues and the liver to respond to insulin. This insulin resistance is frequently found in diabetes and is particularly critical in Type – II diabetes where it aggravates the secretory deformities (Scanlon et al., 2009). A person with diabetes has high blood glucose either because they are not producing enough insulin, or because the body does not respond appropriately to insulin.

Diabetes is considered the world’s one of the biggest health emergencies of the 21st century. A number of people living with this condition are progressively increasing each year. According to an estimate of International Diabetes Federation (IDF, 2015), there are now 415 million people aged between 20 to 79 with diabetes worldwide. IDF estimated a further 318 million individuals with impaired glucose tolerance, which gradually increases the risk of developing the disease in the future. Also, the majority of individuals with diabetes are from developing countries like China (109 million) and India (69.2 million).

Both Type – I and Type – II diabetes is linked with long-term microvascular complications like retinopathy, nephropathy, and neuropathy. Consistent high blood glucose concentration also leads to macrovascular complications such as heart failure, stroke, disease, and peripheral vascular disease. Other health problems also continue to occur due to glycation such as diabetic foot, osteoporosis, cheiroarthropathy, and cataract. In particular diabetic retinopathy was considered as a diabetes-related health issue that research studies anticipated the time span amongst advancement and diagnosis of diabetes by backward linear regression (Worsley & Simmons, 2010).

According to a recent survey conducted by World Health Organization (WHO), healthcare costs associated with the treatment of health issues due to diabetes amounts to approximately US$ 825 billion dollars per year (NCD, 2016). Diabetes is globally significant and costly complication, and its prevalence is growing at almost epidemic levels. Furthermore, diabetic patients encounter significant decrements in daily activities and quality of life with increasing visual impairment. Hence, novel and innovative ways of identification, diagnosis, treatment and follow-up are essential in the management of this growing problem.

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