AIMC Topic: Microscopy

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Effectiveness of Create ML in microscopy image classifications: a simple and inexpensive deep learning pipeline for non-data scientists.

Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology Oct 14, 2021
Observing chromosomes is a time-consuming and labor-intensive process, and chromosomes have been analyzed manually for many years. In the last decade, automated acquisition systems for microscopic images have advanced dramatically due to advances in ...
Artificial Intelligence Microscopy Deep Learning Image Processing, Computer-Assisted
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Yeast cell segmentation in microstructured environments with deep learning.

Bio Systems Oct 9, 2021
Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data. The challenge is exasperated in the setting of microstructured environments. While deep learning approaches have proven useful for genera...
Microscopy Saccharomyces cerevisiae Deep Learning Neural Networks, Computer
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A review for cell and particle tracking on microscopy images using algorithms and deep learning technologies.

Biomedical journal Oct 7, 2021
Time-lapse microscopy images generated by biological experiments have been widely used for observing target activities, such as the motion trajectories and survival states. Based on these observations, biologists can conclude experimental results or ...
Deep Learning Microscopy Algorithms Humans
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Quantitative neuronal morphometry by supervised and unsupervised learning.

STAR protocols Sep 30, 2021
We present a protocol to characterize the morphological properties of individual neurons reconstructed from microscopic imaging. We first describe a simple procedure to extract relevant morphological features from digital tracings of neural arbors. T...
Microscopy Image Processing, Computer-Assisted Zebrafish Software Machine Learning Animals Neurons
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A Large-Scale Fully Annotated Low-Cost Microscopy Image Dataset for Deep Learning Framework.

IEEE transactions on nanobioscience Sep 30, 2021
This work presents a large-scale three-fold annotated, low-cost microscopy image dataset of potato tubers for plant cell analysis in deep learning (DL) framework which has huge potential in the advancement of plant cell biology research. Indeed, low-...
Databases, Factual Deep Learning Microscopy Image Processing, Computer-Assisted
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Bidirectional Mapping-Based Domain Adaptation for Nucleus Detection in Cross-Modality Microscopy Images.

IEEE transactions on medical imaging Sep 30, 2021
Cell or nucleus detection is a fundamental task in microscopy image analysis and has recently achieved state-of-the-art performance by using deep neural networks. However, training supervised deep models such as convolutional neural networks (CNNs) u...
Neural Networks, Computer Image Processing, Computer-Assisted Microscopy Supervised Machine Learning
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Evaluation of Scopio Labs X100 Full Field PBS: The first high-resolution full field viewing of peripheral blood specimens combined with artificial intelligence-based morphological analysis.

International journal of laboratory hematology Sep 21, 2021
BACKGROUND: Current digital cell imaging systems perform peripheral blood smear (PBS) analysis in limited regions of the PBS and require the support of manual microscopy without achieving full digital microscopy. We report a multicenter study that va...
Humans Artificial Intelligence Microscopy Blood Cell Count Image Processing, Computer-Assisted Reproducibility of Results Blood Cells
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Deep-learning on-chip light-sheet microscopy enabling video-rate volumetric imaging of dynamic biological specimens.

Lab on a chip Sep 14, 2021
Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that throug...
Drosophila Microscopy Larva Animals Deep Learning Image Processing, Computer-Assisted Imaging, Three-Dimensional
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Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning.

Lab on a chip Sep 14, 2021
Particle agglutination assays are widely adopted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic particles are mixed with a test sample that potentially contains the target antigen, as a result of whic...
Agglutination Point-of-Care Testing Deep Learning Holography Microscopy Humans
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Misic, a general deep learning-based method for the high-throughput cell segmentation of complex bacterial communities.

eLife Sep 9, 2021
Studies of bacterial communities, biofilms and microbiomes, are multiplying due to their impact on health and ecology. Live imaging of microbial communities requires new tools for the robust identification of bacterial cells in dense and often inter-...
Microbiota Models, Biological High-Throughput Screening Assays Microscopy Deep Learning Bacterial Physiological Phenomena Species Specificity Biofilms
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