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The morphometric parameters of the corneal endothelium – cell density (ECD), cell size variation (CV), and hexagonality (HEX) – provide clinically relevant information about the cornea. To estimate these parameters, the endothelium is commonly imaged with a non-contact specular microscope and cell segmentation is performed to these images. In previous work, we have developed several methods that, combined, can perform an automated estimation of the parameters: the inference of the cell edges, the detection of the region of interest (ROI), a post-processing method that combines both images (edges and ROI), and a refinement method that removes false edges. In this work, we first explore the possibility of using a CNN-based regressor to directly infer the parameters from the edge images, simplifying the framework. We use a dataset of 738 images coming from a study related to the implantation of a Baerveldt glaucoma device and a standard clinical care regarding DSAEK corneal transplantation, both from the Rotterdam Eye Hospital and both containing images of unhealthy endotheliums. This large dataset allows us to build a large training set that makes this approach feasible. We achieved a mean absolute percentage error (MAPE) of 4.32% for ECD, 7.07% for CV, and 11.74% for HEX. These results, while promising, do not outperform our previous work. In a second experiment, we explore the use of the CNN-based regressor to improve the post-processing method of our previous approach in order to adapt it to the specifics of each image. Our results showed no clear benefit and proved that our previous post-processing is already highly reliable and robust.
Original languageEnglish
Title of host publication2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
EditorsThomas Penzel
Place of PublicationPiscataway, NJ, USA
ISBN (Electronic)978-1-5386-1311-5
Publication statusPublished - 2019
EventEngineering in Medicine and Biology Society (EMBC), Annual International Conference of the IEEE - Berlin
Duration: 23 Jul 201927 Jul 2019


ConferenceEngineering in Medicine and Biology Society (EMBC), Annual International Conference of the IEEE
Internet address

ID: 66739924