IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Methods and Programs in Biomedicine
FABC: retinal vessel segmentation using adaboost
IEEE Transactions on Information Technology in Biomedicine
Automatic neuron tracing in volumetric microscopy images with anisotropic path searching
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Vascular tree segmentation in retinal angiographies: deformable contour model approach
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Miar'06 Proceedings of the Third international conference on Medical Imaging and Augmented Reality
Blood vessel segmentation methodologies in retinal images - A survey
Computer Methods and Programs in Biomedicine
Pattern Recognition Letters
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This group published fast algorithms for automatic tracing (vectorization) of the vasculature in live retinal angiograms, and for the extraction of visual landmarks formed by vascular bifurcations and crossings. These landmarks are used for feature-based image matching for controlling a computer-assisted laser retinal surgery instrument under development. This paper describes methods to schedule the vascular tracing computations to maximize the rate of growth of quality of the partial tracing results within a frame cycle. There are two main advantages. First, progressive image matching from partially extracted landmark sets can be faster, and provide an earlier indication of matching failure. Second, the likelihood of successful image matching is greatly improved since the extracted landmarks are of the highest quality for the given computational budget. The scheduling method is based on quantitative measures for the computational work and the quality of landmarks. A coarse grid-based analysis of the image is used to generate seed points for the tracing computations, along with estimates of local edge strengths, orientations, and vessel thickness. These estimates are used to define criteria for real-time preemptive scheduling of the tracing computations.