Model Based Detection of Branching Structures
نویسندگان
چکیده
This paper presents a method for modelling and estimating 2D or 3D branching structures, such as blood vessel bifurcations from medical images. Branches are modelled as a superposition of Gaussian functions in a local region which describe the amplitude, position and orientations of intersecting linear features. The centroids of component features are separated by applying K-means to the local Fourier phase and the covariances and amplitudes subsequently estimated by a likelihood maximisation. A penalised likelihood test, the Akakie Information Criteria (AIC), is employed to select the best fit model in a region. Experimental results are presented on 2D retinal images and synthetic 3D data.
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تاریخ انتشار 2011