Abstract
A retinal image presents three important structures in a healthy eye: optic disk, fovea and blood vessels. These are diseases associated with changes in each of these structures. Some parameters should be extracted in order to evaluate if an eye is healthy. For example, the level of imperfection of the optic disk’s circle contour is related with glaucoma. Furthermore, the proximity of the lesion in the retina to the fovea (structure responsible for the central vision) induces loss of vision. Advanced stages of diabetic retinopathy cause the formation of micro blood vessels that increase the risk of detachment of the retina or prevent light from reaching the fovea. On the other hand, the arterio-venous ratio calculated through the thickness of the central vein and artery of the retina, is a parameter extracted from the vessels segmentation. In image processing, each structure detected has special importance to detect the others, since each one can be used as a landmark to the others. Moreover, often masking the optic disk is crucial to reach good results with algorithms to detect other structures. The performance of the detection algorithms is highly related with the quality of the image and with the existence of lesions. These issues are discussed below.
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Pinão, J., Oliveira, C.M., Mora, A., Dias, J. (2013). Detection of Anatomic Structures in Retinal Images. In: Tavares, J., Natal Jorge, R. (eds) Topics in Medical Image Processing and Computational Vision. Lecture Notes in Computational Vision and Biomechanics, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0726-9_13
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