ArticleBioinformatics (Oxford, England)2020
3D-Cell-Annotator: an open-source active surface tool for single-cell segmentation in 3D microscopy images.
Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- Universal consensus 3D segmentation of cells from 2D segmented stacks.Nature methods · 2025Article
- Gut Analysis Toolbox - automating quantitative analysis of enteric neurons.Journal of cell science · 2024Article
- Label-free live cell recognition and tracking for biological discoveries and translational applications.Npj imaging · 2024Review
- Two-dimensional segmentation fusion tool: an extensible, free-to-use, user-friendly tool for combining different bidimensional segmentations.Frontiers in bioengineering and biotechnology · 2024Article
- High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology with Cellos.Nature communications · 2023Article
- Stiffness-Controlled Hydrogels for 3D Cell Culture Models.Polymers · 2022Article
- A comprehensive review of computational and image analysis techniques for quantitative evaluation of striated muscle tissue architecture.Biophysics reviews · 2022Review
- Marker-controlled watershed with deep edge emphasis and optimized H-minima transform for automatic segmentation of densely cultivated 3D cell nuclei.BMC bioinformatics · 2022Article
- Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential.Frontiers in oncology · 2022Review
- Article
- Analyzing Cell-Scaffold Interaction through Unsupervised 3D Nuclei Segmentation.International journal of bioprinting · 2022Article
- Segmentor: a tool for manual refinement of 3D microscopy annotations.BMC bioinformatics · 2021Article
- Software tools for 3D nuclei segmentation and quantitative analysis in multicellular aggregates.Computational and structural biotechnology journal · 2020Review
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Authors and funding
8 authors.
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Abstract
summarySegmentation 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.
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