ArticleBMC bioinformatics2015
Survey statistics of automated segmentations applied to optical imaging of mammalian cells.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 48 citations in OpenAlex.
- ESQmodel: biologically informed evaluation of 2-D cell segmentation quality in multiplexed tissue images.Bioinformatics (Oxford, England) · 2024Article
- Impact of Training Data, Ground Truth and Shape Variability in the Deep Learning-Based Semantic Segmentation of HeLa Cells Observed with Electron Microscopy.Journal of imaging · 2023Article
- GEMA-An Automatic Segmentation Method for Real-Time Analysis of Mammalian Cell Growth in Microfluidic Devices.Journal of imaging · 2022Article
- Cells/colony motion of oral keratinocytes determined by non-invasive and quantitative measurement using optical flow predicts epithelial regenerative capacity.Scientific reports · 2021Article
- ChipSeg: An Automatic Tool to Segment Bacterial and Mammalian Cells Cultured in Microfluidic Devices.ACS omega · 2021Article
- Deep learning for cellular image analysis.Nature methods · 2019Review
- Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy.Journal of imaging · 2019Article
- Automated sensing and splitting of stem cell colonies on microraft arrays.APL bioengineering · 2019Article
- Separating Touching Cells Using Pixel Replicated Elliptical Shape Models.IEEE transactions on medical imaging · 2019Article
- Three-Dimensional Segmentation and Reconstruction of Neuronal Nuclei in Confocal Microscopic Images.Frontiers in neuroanatomy · 2019Article
- Strategies for robust and accurate experimental approaches to quantify nanomaterial bioaccumulation across a broad range of organisms.Environmental science. Nano · 2019Article
- Quantitative morphometric analysis of adult teleost fish by X-ray computed tomography.Scientific reports · 2018Article
- Modeling, validation and verification of three-dimensional cell-scaffold contacts from terabyte-sized images.BMC bioinformatics · 2017Article
- A novel measure and significance testing in data analysis of cell image segmentation.BMC bioinformatics · 2017Article
- Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments.PLoS computational biology · 2016Article
- Automated Measurement of Cobblestone Morphology for Characterizing Stem Cell Derived Retinal Pigment Epithelial Cell Cultures.Journal of ocular pharmacology and therapeutics : the official journal of the Association for Ocular Pharmacology and Therapeutics · 2016Article
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Corrections and comments
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Authors and funding
12 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications, such cellular measurements are important for understanding cell phenomena, such as cell counts, cell-scaffold interactions, cell colony growth rates, or cell pluripotency stability, as well as for establishing quality metrics for stem cell therapies. In this context, this survey paper is focused on automated segmentation as a software-based measurement leading to quantitative cellular measurements.
methodsWe define the scope of this survey and a classification schema first. Next, all found and manually filteredpublications are classified according to the main categories: (1) objects of interests (or objects to be segmented), (2) imaging modalities, (3) digital data axes, (4) segmentation algorithms, (5) segmentation evaluations, (6) computational hardware platforms used for segmentation acceleration, and (7) object (cellular) measurements. Finally, all classified papers are converted programmatically into a set of hyperlinked web pages with occurrence and co-occurrence statistics of assigned categories.
resultsThe survey paper presents to a reader: (a) the state-of-the-art overview of published papers about automated segmentation applied to optical microscopy imaging of mammalian cells, (b) a classification of segmentation aspects in the context of cell optical imaging, (c) histogram and co-occurrence summary statistics about cellular measurements, segmentations, segmented objects, segmentation evaluations, and the use of computational platforms for accelerating segmentation execution, and (d) open research problems to pursue.
conclusionsThe novel contributions of this survey paper are: (1) a new type of classification of cellular measurements and automated segmentation, (2) statistics about the published literature, and (3) a web hyperlinked interface to classification statistics of the surveyed papers at https://isg.nist.gov/deepzoomweb/resources/survey/index.html.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.