3D-Cell-Annotator: an open-source active surface tool for single-cell segmentation in 3D microscopy images

Ervin A Tasnadi, Timea Toth, Maria Kovacs, Akos Diosdi, Francesco Pampaloni, Jozsef Molnar, Filippo Piccinini, Peter Horvath

Research output: Contribution to journalArticlepeer-review

Abstract

SUMMARY: Segmentation of single cells in microscopy images is one of the major challenges in computational biology. It is the first step of most bioimage analysis tasks, and essential to create training sets for more advanced deep learning approaches. Here, we propose 3D-Cell-Annotator to solve this task using 3D active surfaces together with shape descriptors as prior information in a semi-automated fashion. The software uses the convenient 3D interface of the widely used Medical Imaging Interaction Toolkit (MITK). Results on 3D biological structures (e.g. spheroids, organoids and embryos) show that the precision of the segmentation reaches the level of a human expert.

AVAILABILITY AND IMPLEMENTATION: 3D-Cell-Annotator is implemented in CUDA/C++ as a patch for the segmentation module of MITK. The 3D-Cell-Annotator enabled MITK distribution can be downloaded at: www.3D-cell-annotator.org. It works under Windows 64-bit systems and recent Linux distributions even on a consumer level laptop with a CUDA-enabled video card using recent NVIDIA drivers.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish
Pages (from-to)2948-2949
Number of pages2
JournalBioinformatics (Oxford, England)
Volume36
Issue number9
DOIs
Publication statusPublished - May 1 2020

Keywords

  • Computational Biology
  • Humans
  • Imaging, Three-Dimensional
  • Microscopy
  • Software

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