Automated segmentation of the central serous chorioretinopathy fluid regions using optical coherence tomography scans

Abstract

[Abstract]: Central serous chorioretinopathy is one of the most frequent causes of vision impairment among middle-aged adults. Optical Coherence Tomography (OCT) is a non-invasive diagnostic technique that is commonly used for the monitoring of this relevant eye disease. In this context, this paper proposes a fully automatic system for the characterization of intraretinal pathological fluid regions associated with central serous chori-oretinopathy using OCT scans. To achieve this, we adapted an end-to-end fully convolutional architecture for semantic pixel-wise segmentation. The proposed methodology was tested using a heterogeneous set of 100 OCT scans of different patients. Satisfactory results were obtained, reaching values of 0.9954pm 0.0007, 0.8792 \pm 0.0079 and 0.9651 \pm 0.0041 for the mean Accuracy, mean Jaccard index and mean Dice coefficient, respectively. The proposed system also demonstrated its competitive performance with respect to other state-of-the-art approaches.