Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

The role of extracellular matrix macromolecules in cancer and diabetic macroangiopathy – with special reference to decorin and hyaluronan

The central role of extracellular matrix (ECM) macromolecules in diseases such as cancer and atherosclerotic vascular diseases including diabetic macroangiopathy is indisputable. Decorin and hyaluronan (HA) represent vital ECM macromolecules in the microenvironment of cells and are centrally involved in human cancer and cardiovascular biology. In cancer, decorin is considered to play a tumor suppressive role. However, there is some discrepancy whether malignant cells express it. Regarding HA, its contribution to the development of atherosclerotic vascular diseases has been well established. Nevertheless, the precise role of HA in arterial narrowing associated with diabetes is not known. The present study focused on two vital ECM macromolecules, namely decorin and HA. First, decorin expression was studied in human tumorigenesis. Furthermore, the effect of adenovirus-mediated decorin transduction on selected cancer cell lines was investigated. The results invariably showed that cancer cells completely lacked decorin expression. The study also demonstrated that transducing cancer cells with decorin adenoviral vector markedly inhibited their malignant behavior. In line with this, a strong induction of decorin expression in normal human embryonic stem cells (hESCs), but not in abnormal hESCs was observed during their differentiation. Secondly, the significance of HA in the development of diabetic macroangiopathy in response to hyperglycemia was evaluated. Results showed that the synthesis of HA by vascular smooth muscle cells was significantly increased in response to high glucose concentration. This increase was associated with the diminished ability of the cells to contract collagen-rich matrix suggesting that HA participates in the disturbed vascular remodeling of diabetic patients. The results of this study support endeavours to develop novel ECM macromolecule -based therapies targeting cancer and cardiovascular diseases.