Retinal thickness measurements in optical coherence tomography using a Markov boundary model

We present a highly accurate, robust system for measuring retinal thickness in optical coherence tomography (OCT) images. OCT is a relatively new imaging modality giving cross sectional images that are qualitatively similar to ultrasound but with 10 μm resolution. We begin with a 1-dimensional edge detection kernel to yield edge primitives, which are then selected, corrected, and grouped to form a coherent boundary by use of a Markov model of retinal structure. We have tested the system extensively, and only one of 650 evaluation images caused the algorithm to fail. The anticipated clinical application for this work is the automatic determination of retinal thickness. A careful quantitative evaluation of the system performance over a 1 mm region near the fovea reveals that in more than 99% of the cases, the automatic and manual measurements differed by less than 25 μm (below clinical significance), and in 89% of the tests the difference was less than 10 μm (near the resolution limit). Current clinical practice involves only a qualitative, visual assessment of retinal thickness. Therefore, a robust, quantitatively accurate system should significantly improve patient care