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- W3091521255 abstract "Super Resolution (SR) microscopy leverages a variety of optical and computational techniques for overcoming the optical diffraction limit to acquire additional 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 in surface separation while providing a tensor field to overcome these confounding features. The proposed technique leverages perceptual grouping to generate a tensor field that enables robust evolution of active contours despite ill-defined membrane boundaries." @default.
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- W3091521255 date "2020-01-01" @default.
- W3091521255 modified "2023-09-25" @default.
- W3091521255 title "Segmenting Continuous but Sparsely-Labeled Structures in Super-Resolution Microscopy Using Perceptual Grouping" @default.
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- W3091521255 doi "https://doi.org/10.1007/978-3-030-59722-1_14" @default.
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