Spherical Harmonics For Shape-Constrained 3d Cell Segmentation

Abstract

Recent microscopy imaging techniques allow to precisely analyze cell morphology in 3D image data. To process the vast amount of image data generated by current digitized imaging techniques, automated approaches are demanded more than ever. Segmentation approaches used for morphological analyses, however, are often prone to produce unnaturally shaped predictions, which in conclusion could lead to inaccurate experimental outcomes. In order to minimize further manual interaction, shape priors help to constrain the predictions to the set of natural variations. In this paper, we show how spherical harmonics can be used as an alternative way to inherently constrain the predictions of neural networks for the segmentation of cells in 3D microscopy image data. Benefits and limitations of the spherical harmonic representation are analyzed and final results are compared to other state-of-the-art approaches on two different data sets.

Authors 4

1. Dennis Eschweiler Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

   Institute of Imaging and Computer Vision RWTH Aachen University, Aachen, Germany

2. Malte Rethwisch Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

   Institute of Imaging and Computer Vision RWTH Aachen University, Aachen, Germany

3. Simon Koppers Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

   Institute of Imaging and Computer Vision RWTH Aachen University, Aachen, Germany

4. Johannes Stegmaier Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany

   Institute of Imaging and Computer Vision RWTH Aachen University, Aachen, Germany