Litcius/Paper detail

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

Ervin Tasnádi, Tímea Tóth, Mária Kovács, Ákos Diósdi, Francesco Pampaloni, József Molnár, Filippo Piccinini, Péter Horváth

2020Bioinformatics32 citationsDOIOpen Access PDF

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.

Topics & Concepts

Computer scienceLaptopSegmentationCUDASoftwareInterface (matter)Artificial intelligenceImage segmentationComputer graphics (images)Computer visionPattern recognition (psychology)Programming languageOperating systemMaximum bubble pressure methodBubbleCell Image Analysis TechniquesSingle-cell and spatial transcriptomicsDigital Imaging for Blood Diseases