AIMC Topic: Cell Nucleus

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High-throughput label-free detection of DNA-to-RNA transcription inhibition using brightfield microscopy and deep neural networks.

Computers in biology and medicine Apr 4, 2021
Drug discovery is in constant evolution and major advances have led to the development of in vitro high-throughput technologies, facilitating the rapid assessment of cellular phenotypes. One such phenotype is immunogenic cell death, which occurs part...
DNA RNA Microscopy Cell Nucleus Neural Networks, Computer Image Processing, Computer-Assisted
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A deep learning segmentation strategy that minimizes the amount of manually annotated images.

F1000Research Mar 30, 2021
Deep learning has revolutionized the automatic processing of images. While deep convolutional neural networks have demonstrated astonishing segmentation results for many biological objects acquired with microscopy, this technology's good performance ...
Deep Learning Image Processing, Computer-Assisted Semantics Cell Nucleus Humans Neural Networks, Computer
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A multi-phase deep CNN based mitosis detection framework for breast cancer histopathological images.

Scientific reports Mar 18, 2021
The mitotic activity index is a key prognostic measure in tumour grading. Microscopy based detection of mitotic nuclei is a significant overhead and necessitates automation. This work proposes deep CNN based multi-phase mitosis detection framework "M...
Datasets as Topic Automation Cell Nucleus Mitosis Image Processing, Computer-Assisted Neoplasm Grading Benchmarking Female Humans Mitotic Index Neural Networks, Computer Breast Neoplasms
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DeepACSON automated segmentation of white matter in 3D electron microscopy.

Communications biology Feb 10, 2021
Tracing the entirety of ultrastructures in large three-dimensional electron microscopy (3D-EM) images of the brain tissue requires automated segmentation techniques. Current segmentation techniques use deep convolutional neural networks (DCNNs) and r...
Male Imaging, Three-Dimensional Rats Brain Injuries, Traumatic Artificial Intelligence Reproducibility of Results Animals Microscopy, Electron White Matter Nerve Fibers, Myelinated Mitochondria Image Interpretation, Computer-Assisted Cell Nucleus Rats, Sprague-Dawley Disease Models, Animal Predictive Value of Tests
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DeepCell Kiosk: scaling deep learning-enabled cellular image analysis with Kubernetes.

Nature methods Jan 4, 2021
Deep learning is transforming the analysis of biological images, but applying these models to large datasets remains challenging. Here we describe the DeepCell Kiosk, cloud-native software that dynamically scales deep learning workflows to accommodat...
Workflow Cell Nucleus Cloud Computing Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging Software Algorithms Humans
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Machine-Learning-Based Approach to Decode the Influence of Nanomaterial Properties on Their Interaction with Cells.

ACS applied materials & interfaces Dec 29, 2020
In an nanotoxicity system, cell-nanoparticle (NP) interaction leads to the surface adsorption, uptake, and changes into nuclei/cell phenotype and chemistry, as an indicator of oxidative stress, genotoxicity, and carcinogenicity. Different types of n...
Gold Metal Nanoparticles Dogs Carbon Animals Madin Darby Canine Kidney Cells Machine Learning Cell Nucleus Epithelial Cells Cell Nucleus Shape Cell Proliferation Tight Junctions Actin Cytoskeleton Zonula Occludens-1 Protein Dendrimers
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Cellpose: a generalist algorithm for cellular segmentation.

Nature methods Dec 14, 2020
Many biological applications require the segmentation of cell bodies, membranes and nuclei from microscopy images. Deep learning has enabled great progress on this problem, but current methods are specialized for images that have large training datas...
Deep Learning Humans Image Processing, Computer-Assisted Mice Female Cell Nucleus Animals Neural Networks, Computer Mice, Inbred C57BL Male Software Neurons Algorithms
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Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments.

Nature communications Dec 7, 2020
Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy's utility. Recently, it has been shown t...
Cell Compartmentation Intracellular Space Microscopy, Interference Time-Lapse Imaging CHO Cells Humans Cricetulus Microscopy, Fluorescence Animals Artificial Intelligence Cytoplasm Algorithms Cell Line, Tumor Cell Nucleus Microscopy, Phase-Contrast Reproducibility of Results Hep G2 Cells Cricetinae
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A Deep Learning Pipeline for Nucleus Segmentation.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Nov 19, 2020
Deep learning is rapidly becoming the technique of choice for automated segmentation of nuclei in biological image analysis workflows. In order to evaluate the feasibility of training nuclear segmentation models on small, custom annotated image datas...
Deep Learning Image Processing, Computer-Assisted Cell Nucleus
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NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images.

Computers in biology and medicine Nov 3, 2020
The nuclei segmentation of hematoxylin and eosin (H&E) stained histopathology images is an important prerequisite in designing a computer-aided diagnostics (CAD) system for cancer diagnosis and prognosis. Automated nuclei segmentation methods enable ...
Cell Nucleus Liver Neoplasms Humans Neural Networks, Computer India Deep Learning Image Processing, Computer-Assisted
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