New metaheuristic approaches for the edge-weighted k-cardinality tree problem
Computers and Operations Research
Tracking of Blood Vessels in Retinal Images Using Kalman Filter
DICTA '08 Proceedings of the 2008 Digital Image Computing: Techniques and Applications
Automated Delineation of Dendritic Networks in Noisy Image Stacks
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Obtaining optimal k-cardinality trees fast
Journal of Experimental Algorithmics (JEA)
Marked point process for vascular tree extraction on angiogram
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
IEEE Transactions on Information Technology in Biomedicine
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We present a novel approach to fully automated reconstruction of tree structures in noisy 2D images. Unlike in earlier approaches, we explicitly handle crossovers and bifurcation points, and impose geometric constraints while optimizing a global cost function. We use manually annotated retinal scans to evaluate our method and demonstrate that it brings about a very substantial improvement.