Automatic image processing applied to corneal endothelium cell count and shape characterization
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AutorVelázquez Blázquez, José Sebastián; Cavas Martínez, Francisco; Campuzano Brando, Víctor Andrés; Alió del Barrio, Jorge Luis; Fernández Cañavate, Francisco José; [et al.]
Área de conocimientoExpresión Gráfica en Ingeniería
PatrocinadoresThis work was supported by the Thematic Network for Co-Operative Research in Health (RETICS-RD16/0008/0012), financed by the Carlos III Health Institute and the European Regional Development Fund (FEDER).
Fecha de publicación2020
EditorialFederación de Asociaciones de Ingenieros Industriales de España
Cita bibliográficaVELÁZQUEZ-BLÁZQUEZ, José Sebastián, CAVAS-MARTÍNEZ, Francisco, CAMPUZANO-BRANDO, Victor Andrés et al. AUTOMATIC IMAGE PROCESSING APPLIED TO CORNEAL ENDOTHELIUM CELL COUNT AND SHAPE CHARACTERIZATION. DYNA, March 2020, vol. 95, no. 2, p.170-174. DOI: https://doi.org/10.6036/9275
Graphics User Interface (GUI)
Opening-Closing by reconstruction (OCBR)
Corneal endothelium cell count, as well as cell hexagonality percent characterization, are of great importance nowadays to detect anomalies and pathologies of human eye, such as glaucoma. Prevalent technologies used are mainly based in both microscopy and a later image analysis. However, automatic cell count made by microscopes’ built-in software is rather inconsistent, therefore many laboratories opt for using manual count as the most reliable alternative. This count is a tedious and time-consuming task, that can lead to human error, for this reason, several proposals to automate the process have been made. Present communication shows a procedure for the automatic pre-processing, segmentation and analysis of the images obtained by a confocal microscope, using watershed transform, and the graphics user interface (GUI) created with Matlab® to apply this procedure. In order to quantify the procedure’s quality, 30 corneal endothelium images with a number of cells between 90 and 170 were ...
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