Anatomically constrained maximum likelihood estimation for estimating retinal thickness from scanning laser ophthalmoscope data

Timothy J. Holmes, Brian Northan, Gerhard Zinser, Natalie Hutchings, Ying Li, Dirk-Uwe Bartsch, John G. Flanagan

Abstract: A multistage algorithm is presented, whose components are based upon maximum likelihood estimation (MLE). From 3D scanning laser ophthalmoscope (SLO) image data, the algorithm finds the positions of the two anatomical boundaries of the eye's fundus that define the retina, which are the internal limiting membrane (ILM) and the retinal pigment epithelium (RPE). he retinal thickness is then calculated by subtraction. Retinal thickness is useful for indicating, assessing risk of, and following several diseases, including various forms of macular edema and cysts.