This article presents a novel photoreceptor detection algorithm applied to in-vivo Adaptive Optics (AO) images of the retina obtained from an advanced ophthalmic diagnosis device. Our algorithm is based on a recursive construction of thresholded connected components when the seeds of the recursions are the regional maxima of the image. This algorithm results in a labeling of the AO image which is then used to segment the image with a marker-controlled watershed algorithm. This method has been implemented in a software currently used by medical experts, and preliminary results are very encouraging.
['Kevin Loquin', 'Isabelle Bloch', 'Kiyoko Nakashima', 'Florence Rossant', 'Michel Paques']
Photoreceptor detection in in-vivo Adaptive Optics images of the retina: Towards a simple interactive tool for the physicians