AIMC Topic: Cell Nucleus

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3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis.

NPJ systems biology and applications Oct 20, 2020
During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To ac...
Neural Networks, Computer Animals Imaging, Three-Dimensional Embryo, Mammalian Embryonic Development Cell Nucleus Mice Microscopy, Fluorescence
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LncLocation: Efficient Subcellular Location Prediction of Long Non-Coding RNA-Based Multi-Source Heterogeneous Feature Fusion.

International journal of molecular sciences Oct 1, 2020
Recent studies uncover that subcellular location of long non-coding RNAs (lncRNAs) can provide significant information on its function. Due to the lack of experimental data, the number of lncRNAs is very limited, experimentally verified subcellular l...
Datasets as Topic Cell Nucleus Gene Expression Regulation RNA, Long Noncoding Humans Cytoplasm Benchmarking Computational Biology Ribosomes Software Exosomes Support Vector Machine Animals Base Sequence Eukaryotic Cells Databases, Genetic Genome, Human Terminology as Topic
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NuSeT: A deep learning tool for reliably separating and analyzing crowded cells.

PLoS computational biology Sep 14, 2020
Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learni...
Image Processing, Computer-Assisted Computational Biology Microscopy Software Algorithms Deep Learning HeLa Cells Artifacts Cell Nucleus Humans
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Automatic Detection Method for Cancer Cell Nucleus Image Based on Deep-Learning Analysis and Color Layer Signature Analysis Algorithm.

Sensors (Basel, Switzerland) Aug 7, 2020
Exploring strategies to treat cancer has always been an aim of medical researchers. One of the available strategies is to use targeted therapy drugs to make the chromosomes in cancer cells unstable such that cell death can be induced, and the elimina...
Algorithms Neoplasms Deep Learning Image Processing, Computer-Assisted Cell Nucleus Neural Networks, Computer
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Triple U-net: Hematoxylin-aware nuclei segmentation with progressive dense feature aggregation.

Medical image analysis Jul 18, 2020
Nuclei segmentation is a vital step for pathological cancer research. It is still an open problem due to some difficulties, such as color inconsistency introduced by non-uniform manual operations, blurry tumor nucleus boundaries and overlapping tumor...
Staining and Labeling Cell Nucleus Eosine Yellowish-(YS) Neural Networks, Computer Hematoxylin
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Keras R-CNN: library for cell detection in biological images using deep neural networks.

BMC bioinformatics Jul 11, 2020
BACKGROUND: A common yet still manual task in basic biology research, high-throughput drug screening and digital pathology is identifying the number, location, and type of individual cells in images. Object detection methods can be useful for identif...
Cell Nucleus Plasmodium vivax Deep Learning Image Processing, Computer-Assisted Humans Software
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Deep Learning Identifies Cardiomyocyte Nuclei With High Precision.

Circulation research Jun 3, 2020
Mice Fluorescent Dyes Troponin T Integrases Indoles Microscopy Animals Deep Learning Image Processing, Computer-Assisted Mice, Transgenic Biomarkers Myocytes, Cardiac Myosin Heavy Chains Reproducibility of Results Cell Nucleus Immunohistochemistry
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nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer.

Cell systems May 7, 2020
Single-cell segmentation is typically a crucial task of image-based cellular analysis. We present nucleAIzer, a deep-learning approach aiming toward a truly general method for localizing 2D cell nuclei across a diverse range of assays and light micro...
Deep Learning Microscopy Cell Nucleus
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Robust classification of cell cycle phase and biological feature extraction by image-based deep learning.

Molecular biology of the cell Apr 22, 2020
Across the cell cycle, the subcellular organization undergoes major spatiotemporal changes that could in principle contain biological features that could potentially represent cell cycle phase. We applied convolutional neural network-based classifier...
Cell Cycle Cell Line Deep Learning Microtubules Golgi Apparatus Humans Microscopy, Fluorescence Image Processing, Computer-Assisted Cell Nucleus Animals HeLa Cells Mice NIH 3T3 Cells
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Cellular community detection for tissue phenotyping in colorectal cancer histology images.

Medical image analysis Apr 13, 2020
Classification of various types of tissue in cancer histology images based on the cellular compositions is an important step towards the development of computational pathology tools for systematic digital profiling of the spatial tumor microenvironme...
Neural Networks, Computer Tumor Microenvironment Algorithms Humans Cell Nucleus Colorectal Neoplasms Histological Techniques
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