CHAPTER 2 LITERATURE REVIEW

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Delilah Stevens
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1 CHAPTER 2 LITERATURE REVIEW 2.1 Introduction The retina is a light-sensitive tissue lining the inner surface of the eye. The optics of the eye create an image of the visual world on the retina, which serves much the same function as the film in a camera. Light striking the retina initiates a cascade of chemical and electrical events that ultimately trigger nerve impulses. These are sent to various visual centers of the brain through the fibers of the optic nerve which transmit visual informations from the reina to brain. The retina is considered part of the central nervous system (CNS).The CNS is the part of the nervous system that integrates the information that it receives from, and coordinates the activity of all parts of the body. It is the only part of the ens that can be visualized non-invasively [80]. The pathological information contained in the retina of human eye can use for the early detection of eye diseases such as glaucoma, central serous retinopathy and some of the systemic diseases like diabetes, hypertension and cardiovascular diseases. The lack of physician with ophthalmologic expertise stimulates research in to automatic detection of eye and other diseases from the analysis of retinal fundus images. Many researches have been undertaken in identification and analysis of early sign of pathological changes in the human eye due to various diseases. The advancement of digital image processing and artificial neural network area has made the retinal image analysis more suitable in the diagnosis and classification of diseases as mentioned in chapter!. The advances in image processing mean that there are methods available for pattern recognition of complex images such as those produced from the eye. 12

2 2.2 Present Investigations Diabetes mellitus results in considerable morbidity and mortality, affecting about 180 million every people worldwide every year [80]. However; current statistics suggests that an estimated 50% of diabetes sufferers remain undiagnosed. The total number of people with diabetes is expected to rise to an estimated 300 million cases by the year 2025, with significant increase in developing countries, thought to be the result of population growth, ageing, obesity, and lifestyles. Proportionally, the global population is predicted to increase by 64% between 1995 and 2025, compared with diabetes mellitus among adults, which is expected to rise by over 120%. The development of diabetes immediately increases a patient's propensity for developing a broad spectrum of irreversible complications. Complications of diabetes can be largely divided in to macro vascular and micro vascular complications. The macro vascular complications include cerebrovascular disease, coronary heart disease and peripheral vascular disease. The micro vascular complications include Diabetic Retinopathy (DR), diabetic neuropathy and diabetic nephropathy. The prevalence of these complications is strongly related to the prevalence, type and duration of diabetes; therefore, the increasing global population, changing age demographics, and predicted rise in the proportion of adults suffering from diabetes will inevitably be accompanied by an increase in the frequency of diabetic complications. Diabetes has many manifestations in the eye, of which cataracts and DR are the most significant cause of blindness, and people with diabetes are 25 times more likely than the general population to become blind [9]. Diabetic Retinopathy is the leading cause of blindness in people of working age in the developed world, affecting more than 2% of UK population [25]. In England and Wales, approximately 1000 diabetic patients are registered as blind or partially sighted each year [79] and blindness due to diabetes costs the US Government and general public $500 million annually. A WHO collaborative study projected that the global diabetic burden is expected to increase to 221 million people by 2010 [5]. However, treatment can prevent visual loss if detected early [20]. Thus, early detection through screening facility for patients and 13

3 appropriate referral for therapy is important to preserve vision in individuals with diabetes. Hypertensive retinopathy is damage to the retina due to high blood pressure.when the blood pressure is excessively higher over prolonged time, the small blood vessels in the retina of the eye are damaged. Most of the patients with hypertensive retinopathy have no visual symptoms, however, some may have decreased vision. Signs of damage to the retina caused by hypertension include:arteriolar narrowing, Arteriovenous crossing (Tortuosity), Cotton Wool spots, Hemoorhages. Study of hypertensive retinopathy is thus important, since the hypertensive process will be affecting small vessels throughout the body in a similar manner [45]. Cardiovascular diseases or Heart diseases are class of diseases that involve the heart or blood vessels. Most countries face high and increasing rates of these diseases. When the heart problems are detected, the cause is usually advanced. Therefore early detction of occuring heart diseases is necessary to prevent the heart problems by modifying the risk fctors, such as healthy food, exercise and avoidence of smoking [51]. The blood vessel parmeters of the retina are more suitable to detect the early sign of cardiovascular diseases, since it is possible to detect the risk level of diseases like diabetes and hypertension from the retinal parameters. Central serous retinopathy (CSR), disease usually in one eye, mostly affecting persons in the age group 20 to 50.When the disorder is active it is characterized by leakage of fluid under the retina that has a propensity to accumulate under the central macula. This results in blurred or distorted vision. A blurred or gray spot in the central visual field is common when the retina is detached. Reduced visual acuity may persist after the fluid has disappeared.the diagnosis usually starts with a dilated examination of the retina, followed with confirmation by optical coherence tomography and fluorescein angiography. The angiography test will usually show one or more fluorescent spots with fluid leakage [8]. 14

4 Glaucoma is an eye disorder in which the optic nerve suffers damage, permanently damaging vision in the affected eyes and progressing to complete blindness if untreated. It is often, but not always, associated with increased pressure of the fluid in the eye. The term 'ocular hypertension' is used for cases having constantly raised intraocular pressure (lop) without any associated optic nerve damage. The nerve damage involves loss of retinal ganglion cells in a characteristic pattern. There are many different sub-types of glaucoma but they can all be considered a type of optic neuropathy. Raised intraocular pressure is a significant risk factor for developing glaucoma. Glaucoma can be divided roughly into two main categories, "open angle" and "closed angle" glaucoma. Open angle, chronic glaucoma tends to progress at a slower rate and the patient may not notice that they have lost vision until the disease has progressed significantly.closed angle glaucoma can appear suddenly and is often painful; visual loss can progress quickly but the discomfort often leads patients to seek medical attention before permanent damage occurs. Open-angle glaucoma accounts for 90% of glaucoma cases in the United States. It is painless and does not have acute attacks. Closed-angle glaucoma accounts for less than 10% of glaucoma cases in the United States, but as much as half of glaucoma cases in other nations, particularly Asian countries. Glaucoma has been nicknamed the "silent thief of sight" because the loss of vision normally occurs gradually over a long period of time and is often only recognized when the disease is quite advanced. Once lost, this damaged visual field cannot be recovered. If the condition is detected early enough it is possible to arrest the development or slow the progression with medical and surgical means [33]. There is increasing evidence that ocular blood flow is involved in the pathogenesis of glaucoma. Current data indicate that fluctuations in blood flow are more harmful in glaucomatous optic neuropathy than steady reductions. Unstable blood pressure is linked to optic nerve head damage and correlate with visual field deterioration. Screening for glaucoma is usually performed as part of a standard eye examination performed by ophthalmologists. Exanination for glaucoma should include measurements of the intraocular pressure, changes in size or shape of the eye, damges 15

5 to the optic nerve or change in the cup-to- optic disc ratio, rim appearance and vascular change. Of these the retinal nerve fiber layer (RNFL) damages is the important parameter, and can be assessed with imaging techniques such as optical coherence tomography (OCT) [49]. Hence, these investigations reveal that retinal image analysis can be very much useful in diagnosing the eye and other systemic diseases. The imaging of retina screening was performed by well trained personnel using Ophthalmoscope in earlier days. The accuracy of ophthalmoscopy is substantially lower when performed by primary care physicians [58]. As an alternative, seven-field stereoscopic fundus photography is another acceptable method, but also requires both a trained photographer and a trained reader. Fundal photography compares favorably with ophthalmoscopy [57]. Mass screening of persons in remote areas require the camera system and trained ophthalmologist and other medical experts. Whilst screening schemes could reduce the risk of blindness and other diseases to less than half compared with unscreened cases, significant resources are required to put these screening schemes into place [50]. One of the largest sources of expenditure in setting up of screening centers is the cost of financing trained manpower. As a means to reduce this cost, the workload of the manpower is reduced by using computerised expert systems using digitized retinal images. This kind of expert systems are able to exclude a large number of those patients who have no need for further diagnosis, will reduce the workload of the trained medical experts and thus reduce costs. Another benefit of an expert system for detection of diseases is improved repeatability and immunity from fatigue. Great interest over past 10 years has centered on developing methods that detect diseases from retinal images with sufficient sensitivity to be able to implement them into screening schemes as an adjunct to current strategies. Current technology offers no potential for a completely independent automatic detection and diagnosis of these above diseases in a single system that has been tested for acceptable specificity. 16

6 2.2.1 Digital Image Processing A grey-scale digital image may be defined as a two-dimensional function, f(x, y), where x and y are spatial co-ordinates and f the amplitude at any pair of co-ordinates. Pixels surrounding any given pixel constitute its 'neighborhood'. This mathematical means of describing an image is the basis for allowing complex calculations that are termed image processing and analysis. Image processing operations of an image normally falls into one of the three categories: enhancement (improving contrast), restoration (deblurring of an image) and segmentation (isolating particular areas of interest within the image) [31]. The major difficulty in image capture of the ocular fundus is image quality which is affected by factors, such as medial opacities, defocus or presence of artifact. Image enhancement involves the improvement of an image so that the result is more suitable for viewing, processing or analysis Segmentation of retinal images A potential use of fundal digital image analysis is the ability to analyse a large database of fundal images in a short period of time. The identification of fundal landmark features such as the optic disc, fovea and the retinal vessels as reference coordinates is a prerequisite before systems can achieve more complex tasks identifying pathological entities. The techniques exist for identification of these structures in retinal photographs are: Optic nerve head localisation The location of the optic disc is important in retinal image analysis, to locate anatomical components in retinal images, for vessel tracking, as a reference length for measuring distances in retinal images, and for registering changes within the optic disc region due to disease. The optic disc is usually the brightest component on the fundus, and therefore a cluster of high intensity pixels with a high grey-scale value will identify the optic disc location [14]. Other features that help differentiate the 17

7 .' j optic nerve are the confluence of blood vessels at the optic disc, which results in a large variance in intensity of adjacent pixels [70], correctly identified the location of the optic disc employing the variance of intensity between the optic disc and adjacent blood vessels. Model based methods used for localisation, tracking of image structures in [53], to locate the optic disc boundary, and hence the optic disc detection produced good results Localisation of Fovea The fovea can detect by exploiting the avascularity of the fovea, thus having different grey levels at its border [38]. The location of the fovea was chosen as the position of maximum correlation between a model template and the intensity image, obtained from the intensity-hue-saturation transformation, provided it was appropriately placed temporal to the optic disc and in the region of minimum intensity Vascular segmentation Retinal vascular segmentation techniques utilise the contrast existing between the retinal blood vessel and the background. The cross-sectional grey-level profile of a typical vessel conforms to a Gaussian shape, the vasculature is piecewise linear and may be represented by a series of connected line segments and that the vasculature originates from the same point (the optic disc) and all vessels are connected [36] Matched filters This usually employs a two-dimensional linear structural element that has a Gaussian cross-profile section, rotated into three dimensions to identify the cross-profile of the blood vessel, which typically has a Gaussian or a Gaussian derivative profile [13]. The structural element is rotated into many different orientations (usually eight or twelve) to fit into vessels of different configuration. The image is then thresholded (an arbitrary chosen grey level divides all features into a binary classification, 18

8 depending on whether they have a greater or lesser intensity level than the 'brightness threshold') to extract the vessel silhouette from the background. But using too long a structuring element may have difficulty in fitting into highly tortuous vessels. In addition, matched filters do not operate in isolation, but as part of an algorithmic chain, requiring thresholding into a binary vessel/non-vessel image [73] Vessel tracking Another technique for vessel segmentation include "vessel-tracking", whereby vessel centre locations are automatically sought over each cross-section of a vessel along the vessels longitudinal axis, having been given a starting and end point [41]. They tend to work on single retinal vessels and require starting and ending points to be identified by the user. Matched filters [69] accomplish the selection of vascular points Morphological processing Morphological image processing exploits features of the vasculature shape that are known a priori, such as it being piecewise linear and connected. Algorithms that extract linear shapes can be very useful for vessel segmentation. Structuring elements of a certain intensity can be added (dilation) or subtracted (erosion) to the underlying image. Opening (erosion followed by dilatation) with a structuring element of a certain shape can separate objects in an image, by preserving image structures that can contain the structural element and removing those that cannot in the image. Closing (dilatation followed by erosion) can used to 'fill-in' small holes within an image [36]. The above literature survey reveals that there is amble scope for the implementation of latest innovations in to the analysis of retina and related areas. 19

CHAPTER 8 EVALUATION OF FUNDUS IMAGE ANALYSIS SYSTEM

CHAPTER 8 EVALUATION OF FUNDUS IMAGE ANALYSIS SYSTEM Diabetic retinopathy is very common retinal disease associated with diabetes. Efforts to prevent diabetic retinopathy though have yielded some results;