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Convolutional Neural Network-Based Instance Segmentation Algorithm to Acquire Quantitative Criteria of Early Mouse Development

https://doi.org/10.1101/324186
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-60761-404-3_16openalex-snapshot
Imaging of Cellular Oxygen and Analysis of Metabolic Responses of Mammalian Cells
inferredcites →https://doi.org/10.1007/978-3-319-10590-1_40openalex-snapshot
Instance Segmentation of Indoor Scenes Using a Coverage Loss
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46448-0_2openalex-snapshot
SSD: Single Shot MultiBox Detector
inferredcites →https://doi.org/10.1007/978-3-319-46723-8_49openalex-snapshot
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
inferredcites →https://doi.org/10.1007/s11263-019-01228-7openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1016/0012-1606(87)90055-8openalex-snapshot
A quantitative analysis of cell allocation to trophectoderm and inner cell mass in the mouse blastocyst
inferredcites →https://doi.org/10.1016/j.stemcr.2014.01.010openalex-snapshot
A Rapid and Efficient 2D/3D Nuclear Segmentation Method for Analysis of Early Mouse Embryo and Stem Cell Image Data
inferredcites →https://doi.org/10.1016/j.ydbio.2012.01.001openalex-snapshot
Abnormal chromosome segregation at early cleavage is a major cause of the full-term developmental failure of mouse clones
inferredcites →https://doi.org/10.1038/nmeth.1476openalex-snapshot
Fast, high-contrast imaging of animal development with scanned light sheet–based structured-illumination microscopy
inferredcites →https://doi.org/10.1038/nmeth.2062openalex-snapshot
Quantitative high-speed imaging of entire developing embryos with simultaneous multiview light-sheet microscopy
inferredcites →https://doi.org/10.1038/nmeth.4182openalex-snapshot
Prospective identification of hematopoietic lineage choice by deep learning
inferredcites →https://doi.org/10.1073/pnas.0511111103openalex-snapshot
Automated cell lineage tracing in Caenorhabditis elegans
inferredcites →https://doi.org/10.1093/humrep/12.8.1750openalex-snapshot
Intracytoplasmic sperm injection: correlation of oocyte grade based on polar body, perivitelline space and cytoplasmic inclusions with fertilization rate and embryo quality
inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-snapshot
Fully convolutional networks for semantic segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.305openalex-snapshot
Deep Watershed Transform for Instance Segmentation
inferredcites →https://doi.org/10.1109/cvprw.2017.116openalex-snapshot
Nuclei Segmentation of Fluorescence Microscopy Images Using Three Dimensional Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/iccv.2011.6126474openalex-snapshot
Adaptive deconvolutional networks for mid and high level feature learning
inferredcites →https://doi.org/10.1109/iccv.2015.178openalex-snapshot
Learning Deconvolution Network for Semantic Segmentation
inferredcites →https://doi.org/10.1109/tmi.2015.2481436openalex-snapshot
An Automatic Learning-Based Framework for Robust Nucleus Segmentation
inferredcites →https://doi.org/10.1126/science.1162493openalex-snapshot
Reconstruction of Zebrafish Early Embryonic Development by Scanned Light Sheet Microscopy
inferredcites →https://doi.org/10.1145/1553374.1553453openalex-snapshot
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1242/bio.022079openalex-snapshot
Quantitative microscopy uncovers ploidy changes during mitosis in liveDrosophilaembryos and their effect on nuclear size
inferredcites →https://doi.org/10.1262/jrd.20166openalex-snapshot
Long-Term, Six-Dimensional Live-Cell Imaging for the Mouse Preimplantation Embryo That Does Not Affect Full-Term Development
inferredcites →https://doi.org/10.1371/journal.pcbi.1005177openalex-snapshot
Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments
inferredcites →https://doi.org/10.1371/journal.pone.0031638openalex-snapshot
Fluorescence Cell Imaging and Manipulation Using Conventional Halogen Lamp Microscopy
inferredcites →https://doi.org/10.1371/journal.pone.0035550openalex-snapshot
Automatic Extraction of Nuclei Centroids of Mouse Embryonic Cells from Fluorescence Microscopy Images
inferredcites →https://doi.org/10.1371/journal.pone.0101891openalex-snapshot
Improved and Robust Detection of Cell Nuclei from Four Dimensional Fluorescence Images
inferredcites →https://doi.org/10.1371/journal.pone.0150853openalex-snapshot
Object Segmentation and Ground Truth in 3D Embryonic Imaging
inferredcites →https://doi.org/10.48550/arxiv.1012.2599openalex-snapshot
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot
Adam: A Method for Stochastic Optimization

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-030-98950-7_25openalex-snapshot
The Influence of Tissue Architecture on Drug Response: Anticancer Drug Development in High-Dimensional Combinatorial Microenvironment Platforms
inferred← citeshttps://doi.org/10.1016/j.bspc.2019.101726openalex-snapshot
Centroid calculation of the blastomere from 3D Z-Stack image data of a 2-cell mouse embryo
inferred← citeshttps://doi.org/10.1038/s41592-019-0403-1openalex-snapshot
Deep learning for cellular image analysis
inferred← citeshttps://doi.org/10.1093/bioinformatics/btac673openalex-snapshot
SATINN: an automated neural network-based classification of testicular sections allows for high-throughput histopathology of mouse mutants
inferred← citeshttps://doi.org/10.1093/bioinformatics/btz650openalex-snapshot
Multi-scale structural analysis of proteins by deep semantic segmentation
inferred← citeshttps://doi.org/10.1371/journal.pcbi.1009879openalex-snapshot
Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets
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