Transplantation of corneal tissue is a usual practice in hospitals. The analysis of microscopy images of donor corneal endothelium is routinely carried out at eye banks for the clinical assessment of cornea quality and suitability for transplantation. One of the main clinical parameters expressing the health of a cornea, and assessing their suitability as a human graft, is the cell density of its endothelium. Endothelium cell density is conventionally estimated by a long, tedious and error-prone manual counting procedure, carried out by experts who, according to a protocol, observe specimen images through an optical microscope. Besides a great subjectivity, this manual process causes a great disparity in the results derived from the protocol considered. Another additional and very important drawback is that images are often blurred and noisy, what makes very difficult the correct recognition of the cells. Taking into account aforementioned problems, this paper introduces a computer intelligence-based system for automatic segmentation of corneal endothelium images that in addition to facilitating technicians work of will reduce the disparity of results.
展开▼
