AIMC Topic: Cell Nucleus

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Alpha particle microdosimetry calculations using a shallow neural network.

Physics in medicine and biology Jan 25, 2022
A shallow neural network was trained to accurately calculate the microdosimetric parameters, 〈〉 and 〈〉 (the first and second moments of the single-event specific energy spectra, respectively) for use in alpha-particle microdosimetry calculations. The...
Cell Survival Cell Nucleus Monte Carlo Method Neural Networks, Computer Alpha Particles
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A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm.

Scientific reports Jan 21, 2022
Accurate and early detection of anomalies in peripheral white blood cells plays a crucial role in the evaluation of well-being in individuals and the diagnosis and prognosis of hematologic diseases. For example, some blood disorders and immune system...
Humans Prognosis Female Elementary Particles Datasets as Topic Child Cell Nucleus Image Processing, Computer-Assisted Hematologic Diseases Male Leukocytes Cytoplasm Middle Aged Aged Deep Learning Young Adult Adolescent Adult
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Hybrid Convolution Neural Network in Classification of Cancer in Histopathology Images.

Journal of digital imaging Jan 12, 2022
Cancer statistics in 2020 reveals that breast cancer is the most common form of cancer among women in India. One in 28 women is likely to develop breast cancer during their lifetime. The mortality rate is 1.6 to 1.7 times higher than maternal mortali...
Female Breast Neoplasms Male India Humans Neural Networks, Computer Image Processing, Computer-Assisted Cell Nucleus
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Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning.

Nature cell biology Dec 7, 2021
Simultaneous imaging of various facets of intact biological systems across multiple spatiotemporal scales is a long-standing goal in biology and medicine, for which progress is hindered by limits of conventional imaging modalities. Here we propose us...
Cell Membrane Optical Imaging Refractometry Cell Nucleolus HEK293 Cells Cell Nucleus Actins Lipid Droplets Subcellular Fractions Electron Microscope Tomography COS Cells Single-Cell Analysis Imaging, Three-Dimensional Mice Mitochondria Chlorocebus aethiops HeLa Cells 3T3 Cells Humans Animals Deep Learning Cell Line, Tumor
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Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated Melanomas.

The Journal of investigative dermatology Oct 30, 2021
Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. In this study, we utilize two distinct and complementary machine-learning methods of analyzing who...
Mutation Cell Nucleus Proto-Oncogene Proteins B-raf Humans Melanoma Deep Learning
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Detection of malignant melanoma in H&E-stained images using deep learning techniques.

Tissue & cell Sep 29, 2021
Histopathological images are widely used to diagnose diseases including skin cancer. As digital histopathological images are typically of very large size, in the order of several billion pixels, automated identification of all abnormal cell nuclei an...
Image Processing, Computer-Assisted Staining and Labeling Melanoma, Cutaneous Malignant Cell Nucleus Eosine Yellowish-(YS) Hematoxylin Algorithms Melanoma Humans Skin Neoplasms Neural Networks, Computer Deep Learning
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A machine learning approach for single cell interphase cell cycle staging.

Scientific reports Sep 29, 2021
The cell nucleus is a tightly regulated organelle and its architectural structure is dynamically orchestrated to maintain normal cell function. Indeed, fluctuations in nuclear size and shape are known to occur during the cell cycle and alterations in...
Humans Datasets as Topic Cell Nucleus Mice Interphase Support Vector Machine Animals Intravital Microscopy Cell Line Single-Cell Analysis Microscopy, Fluorescence Image Processing, Computer-Assisted
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Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Aug 23, 2021
Image segmentation remains to be one of the most vital tasks in the area of computer vision and more so in the case of medical image processing. Image segmentation quality is the main metric that is often considered with memory and computation effici...
Deep Learning Image Processing, Computer-Assisted Cell Nucleus Neural Networks, Computer Software
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Deep learning to design nuclear-targeting abiotic miniproteins.

Nature chemistry Aug 9, 2021
There are more amino acid permutations within a 40-residue sequence than atoms on Earth. This vast chemical search space hinders the use of human learning to design functional polymers. Here we show how machine learning enables the de novo design of ...
Deep Learning Datasets as Topic Cytosol Cell Nucleus Protein Conformation Protein Transport Proteins Models, Molecular Molecular Weight
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Quick Annotator: an open-source digital pathology based rapid image annotation tool.

The journal of pathology. Clinical research Jul 19, 2021
Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest...
Predictive Value of Tests Pathology Colorectal Neoplasms Microscopy Biopsy Humans High-Throughput Screening Assays Deep Learning Workflow Automation, Laboratory Image Interpretation, Computer-Assisted Time Factors Cell Nucleus Reproducibility of Results Epithelial Cells
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