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Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020; 23rd International C Anne L. Martel,Purang Abolmaesumi,Leo Joskow

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Neuronal Subcompartment Classification and Merge Error Correctionconnected by millions of synapses. Interpreting reconstructions at this scale demands advances in the automated analysis of neuronal morphologies, for example by identifying morphological and functional subcompartments within neurons. We present a method that for the first time uses full 3d input (v
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Leveraging Tools from Autonomous Navigation for Rapid, Robust Neuron Connectivitye. State-of-the-art algorithms are almost entirely dominated by the use of convolutional neural network approaches that may be difficult to run at scale given schedule, cost, and resource limitations. We demonstrate a novel solution for high-resolution electron microscopy brain image volumes that pe
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Segmenting Continuous but Sparsely-Labeled Structures in Super-Resolution Microscopy Using Perceptuadditional spatial details. However, added spatial details challenge existing segmentation tools. Confounding features include protein distributions that form membranes and boundaries, such as cellular and nuclear surfaces. We present a segmentation pipeline that retains the benefits provided by SR i
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DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imagillel and at single-cell resolution. In order to use the data gained with calcium imaging, it is necessary to extract individual cells and their activity from the recordings. We present DISCo, a novel approach for the cell segmentation in calcium imaging videos. We use temporal information from the r
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