Object tracking in SD-OCT images using Kalman filters
Guven, Deniz (2015) Object tracking in SD-OCT images using Kalman filters. [Dissertation (University of Nottingham only)]
In this project a novel approach in segmenting retinal layers in 3D Optical Coherence Tomography images is presented. Using Kalman filter, retinal nerve fiber layer and bacillary layer is segmented by tracking these two layers through slices of a 3D UHR-SD OCT volume. The application of this algorithm to 3D UHR-SD OCT volumes show that it is a viable framework for detecting and tracking NFL and BL layers.
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