1. Fast and memory-efficient LOGISMOS graph search for intraretinal layer segmentation of 3D macular OCT scans

    Fast and memory-efficient LOGISMOS graph search for intraretinal layer segmentation of 3D macular OCT scans

    Image segmentation is important for quantitative analysis of medical image data. Recently, our research group has introduced a 3-D graph search method which can simultaneously segment optimal interacting surfaces with respect to the cost function in volumetric images. Although it provides excellent segmentation accuracy, it is computationally demanding (both CPU and memory) to simultaneously segment multiple surfaces from large volumetric images. Therefore, we propose a new, fast, and memory-efficient graph search method for intraretinal layer segmentation of 3-D macular optical coherence tomograpy (OCT) scans. The key idea is to reduce the size of a graph by combining the nodes with ...

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