Semiautonomous Medical Image Segmentation Using Seeded Cellular Automaton Plus Edge Detector

<table>Comparison of segmentation accuracy for 40 brain MRIs, across three algorithms and three sets of seeds (for which seeds were placed on 1, 3, or 15 image slices). The proposed algorithm, SCAPE, generated segmentations that match the gold standard better than those of Seeded Cellular Automata (SCA) and Graphcut, particularly when minimal seeds were provided. Error bars show standard deviations.</table>

International Scholarly Research Notices

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Figure 2: Semiautonomous Medical Image Segmentation Using Seeded Cellular Automaton Plus Edge Detector 