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Clinical research suggests that changes in the retinal blood vessels (e.g., vessel caliber) are important indicators for earlier diagnosis of diabetes and cardiovascular diseases. Reliable vessel detection or segmentation is a prerequisite for quantifiable retinal blood vessel analysis for predicting these diseases. However, the segmentation of blood vessels is complicated by its huge variations such...
Automated segmentation of retinal vessels in optic fundus images has been the most prevailing effort in many researches during recent years. In this paper, we propose a multi-scale method based on a weighted 2D medialness function. The result of the medialness function is first multiplied by the eigenvalues of the Hessian matrix in every pixel of the image in order to extract vessel's medial-lines...
The cornea is the window of the eye and when it is severely damaged or diseased, vision is impaired. Descemet's Stripping Automated Endothelial Keratoplasty (DSAEK) is a surgical procedure to replace the malfunctioned Descemet's membrane with a healthy one in order to restore the patient's sight. After the operation, ophthalmologists need to monitor the grafted membrane to check for signs of detachment,...
This paper presents an investigation into different approaches for segmentation-driven retinal image registration. This constitutes an intermediate step towards detecting changes occurring in the topography of blood vessels, which are caused by disease progression. A temporal dataset of retinal images was collected from small animals (i.e. mice). The perceived low quality of the dataset employed favoured...
Retinal vessels can show different states of several diseases, making the detection of vessels in retinal images very crucial. Retinal images can be used for other applications such as ocular fundus operations and human recognition. Due to the acquisition process, these images often have low grey level contrast and dynamic range that can seriously affect diagnosis procedure results. In this paper,...
Investigating the effect of retinal oxygenation abnormalities in the development of common eye diseases requires accurate assessment of oxygen tension in retinal vasculatures. Estimation of oxygen tension in retinal capillaries using phosphorescence lifetime imaging is addressed in this paper. Separation from tissue and oxygen tension estimation is a more challenging task for capillaries when compared...
Accurate corneal layer boundary extraction from optical coherence tomograms can provide precise layer thickness measurements required in the analysis of corneal disease. This paper establishes a novel approach to precisely obtain the five primary corneal layer boundaries. The proposed method determines correspondence relationships between the layer boundaries to facilitate robust boundary extraction...
Retinal images are used for automated diagnosis of Diabetic Retinopathy. Preprocessing of retinal image is required prior to detection of features and abnormalities. The objective of preprocessing segmentation is to separate the background and noisy area from the overall image to enhance the quality of acquired retinal image. We present a method for colored retinal image preprocessing and enhancement...
In automated diagnosis of diabetic retinopathy, retinal images are used. The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. Segmentation of retinal images is essential for this purpose. The segmentation is employed to smooth and strengthen images by separating the noisy area from the overall image thus resulting in retinal image enhancement...
Extraction of anatomical structures (landmarks), such as optic disk (OD), fovea and blood vessels, from fundus images is useful in automatic diagnosis. Current approaches largely use spatial relationship among the landmarks' position for detection. In this paper, we present an appearance-based method for detecting fovea and OD from colour images. The strategy used for detection is based on improving...
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