SplineDist: Automated Cell Segmentation with Spline Curves

Mandal, S.; Uhlmann, V.

doi:10.1101/2020.10.27.357640

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bioRxiv · 10.1101/2020.10.27.357640

SplineDist: Automated Cell Segmentation with Spline Curves

Mandal, S.·Uhlmann, V.

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Abstract

We present SplineDist, an instance segmentation convolutional neural network for bioimages extending the popular StarDist method. While StarDist describes objects as star-convex polygons, SplineDist uses a more flexible and general representation by modelling objects as planar parametric spline curves. Based on a new loss formulation that exploits the properties of spline constructions, we can incorporate our new object model in StarDists architecture with minimal changes. We demonstrate in synthetic and real images that SplineDist produces segmentation outlines of equal quality than StarDist with smaller network size and accurately captures non-star-convex objects that cannot be segmented with StarDist.

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Mandal, S., Uhlmann, V.. 2020-10-28. SplineDist: Automated Cell Segmentation with Spline Curves. https://doi.org/10.1101/2020.10.27.357640

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