PT  - JOURNAL ARTICLE
AU  - Ervin A. Tasnadi
AU  - Timea Toth
AU  - Maria Kovacs
AU  - Akos Diosdi
AU  - Francesco Pampaloni
AU  - Jozsef Molnar
AU  - Filippo Piccinini
AU  - Peter Horvath
TI  - 3D-Cell-Annotator: an open-source active surface tool for single cell segmentation in 3D microscopy images
AID  - 10.1101/677294
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 677294
4099  - http://biorxiv.org/content/early/2019/06/20/677294.short
4100  - http://biorxiv.org/content/early/2019/06/20/677294.full
AB  - 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 fully- and 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, 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.Contacts filippo.piccinini{at}irst.emr.it and horvath.peter{at}brc.mta.hu