AIMC Topic: Cell Nucleus

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Semantic segmentation of human cell nucleus using deep U-Net and other versions of U-Net models.

Network (Bristol, England) Jul 12, 2022
The deep learning models play an essential role in many areas, including medical image analysis. These models extract important features without human intervention. In this paper, we propose a deep convolution neural network, named as deep U-Net mode...
Cell Nucleus Semantics Neural Networks, Computer Humans
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SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology Images.

IEEE journal of biomedical and health informatics Jul 1, 2022
Automated nuclei segmentation and classification are the keys to analyze and understand the cellular characteristics and functionality, supporting computer-aided digital pathology in disease diagnosis. However, the task still remains challenging due ...
Humans Cell Nucleus Histological Techniques Image Processing, Computer-Assisted Neural Networks, Computer
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AL-Net: Attention Learning Network Based on Multi-Task Learning for Cervical Nucleus Segmentation.

IEEE journal of biomedical and health informatics Jun 3, 2022
Cervical nucleus segmentation is a crucial and challenging issue in automatic pathological diagnosis due to uneven staining, blurry boundaries, and adherent or overlapping nuclei in nucleus images. To overcome the limitation of current methods, we pr...
Humans Neural Networks, Computer Cell Nucleus Attention Image Processing, Computer-Assisted Cervix Uteri Female
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Machine Learning Methods for Exploring Sequence Determinants of 3D Genome Organization.

Journal of molecular biology Jun 2, 2022
In higher eukaryotic cells, chromosomes are folded inside the nucleus. Recent advances in whole-genome mapping technologies have revealed the multiscale features of 3D genome organization that are intertwined with fundamental genome functions. Howeve...
Genome Chromosomes Cell Nucleus Chromatin Chromosome Mapping Machine Learning Sequence Analysis, DNA Imaging, Three-Dimensional
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Nucleus classification in histology images using message passing network.

Medical image analysis May 14, 2022
Identification of nuclear components in the histology landscape is an important step towards developing computational pathology tools for the profiling of tumor micro-environment. Most existing methods for the identification of such components are li...
Histological Techniques Algorithms Cell Nucleus Neural Networks, Computer Humans
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Microscopic nuclei classification, segmentation, and detection with improved deep convolutional neural networks (DCNN).

Diagnostic pathology Apr 19, 2022
BACKGROUND: Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI).
Neural Networks, Computer Humans Cell Nucleus Image Processing, Computer-Assisted
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Deep learning -- promises for 3D nuclear imaging: a guide for biologists.

Journal of cell science Apr 14, 2022
For the past century, the nucleus has been the focus of extensive investigations in cell biology. However, many questions remain about how its shape and size are regulated during development, in different tissues, or during disease and aging. To trac...
Microscopy Image Processing, Computer-Assisted Deep Learning Neural Networks, Computer Cell Nucleus Imaging, Three-Dimensional
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Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images.

PLoS computational biology Mar 14, 2022
Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep...
Animals Cell Cycle Mice Cell Cycle Proteins Mammals Cell Nucleus Image Processing, Computer-Assisted Deep Learning
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TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classification.

Neural networks : the official journal of the International Neural Network Society Mar 9, 2022
Nuclei segmentation and classification of hematoxylin and eosin-stained histology images is a challenging task due to a variety of issues, such as color inconsistency that results from the non-uniform manual staining operations, clustering of nuclei,...
Distillation Neural Networks, Computer Cluster Analysis Cell Nucleus Image Processing, Computer-Assisted
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Convolutional Blur Attention Network for Cell Nuclei Segmentation.

Sensors (Basel, Switzerland) Feb 18, 2022
Accurately segmented nuclei are important, not only for cancer classification, but also for predicting treatment effectiveness and other biomedical applications. However, the diversity of cell types, various external factors, and illumination conditi...
Image Processing, Computer-Assisted Cell Nucleus Neural Networks, Computer
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