AIMC Topic: Cell Nucleus

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HistoMSC: Density and topology analysis for AI-based visual annotation of histopathology whole slide images.

Computers in biology and medicine Mar 21, 2025
We introduce an end-to-end framework for the automated visual annotation of histopathology whole slide images. Our method integrates deep learning models to achieve precise localization and classification of cell nuclei with spatial data aggregation ...
Humans Deep Learning Image Interpretation, Computer-Assisted Cell Nucleus Image Processing, Computer-Assisted
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Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.

Nature communications Mar 14, 2025
Genetic variants can affect protein function by driving aberrant subcellular localization. However, comprehensive analysis of how mutations promote tumor progression by influencing nuclear localization is currently lacking. Here, we systematically ch...
Deep Learning Carcinogenesis Mutation Humans Neoplasms Nuclear Localization Signals PTEN Phosphohydrolase Cell Nucleus Active Transport, Cell Nucleus Cytoplasm
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SEPO-FI: Deep-learning based software to calculate fusion index of muscle cells.

Computers in biology and medicine Jan 24, 2025
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive cou...
Muscle Fibers, Skeletal Software Animals Image Processing, Computer-Assisted Deep Learning Cell Nucleus Humans
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HistoNeXt: dual-mechanism feature pyramid network for cell nuclear segmentation and classification.

BMC medical imaging Jan 7, 2025
PURPOSE: To develop an end-to-end convolutional neural network model for analyzing hematoxylin and eosin(H&E)-stained histological images, enhancing the performance and efficiency of nuclear segmentation and classification within the digital patholog...
Neural Networks, Computer Image Processing, Computer-Assisted Humans Hematoxylin Cell Nucleus Eosine Yellowish-(YS)
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Unsupervised inter-domain transformation for virtually stained high-resolution mid-infrared photoacoustic microscopy using explainable deep learning.

Nature communications Dec 30, 2024
Mid-infrared photoacoustic microscopy can capture biochemical information without staining. However, the long mid-infrared optical wavelengths make the spatial resolution of photoacoustic microscopy significantly poorer than that of conventional conf...
Fibroblasts Unsupervised Machine Learning Image Processing, Computer-Assisted Infrared Rays Humans Microscopy, Confocal Microscopy Photoacoustic Techniques Deep Learning Cell Nucleus
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Transferable deep learning with coati optimization algorithm based mitotic nuclei segmentation and classification model.

Scientific reports Dec 19, 2024
Image processing and pattern recognition methods have recently been extensively implemented in histopathological images (HIs). These computer-aided techniques are aimed at detecting the attentive biological markers for assisting the final cancer grad...
Cell Nucleus Mitosis Deep Learning Image Processing, Computer-Assisted Algorithms Neoplasms Humans
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Proximity adjusted centroid mapping for accurate detection of nuclei in dense 3D cell systems.

Computers in biology and medicine Dec 17, 2024
In the past decade, deep learning algorithms have surpassed the performance of many conventional image segmentation pipelines. Powerful models are now available for segmenting cells and nuclei in diverse 2D image types, but segmentation in 3D cell sy...
Algorithms Deep Learning Humans Cell Nucleus Spheroids, Cellular Imaging, Three-Dimensional Image Processing, Computer-Assisted
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Comparison between two artificial intelligence models to discriminate cancerous cell nuclei based on confocal fluorescence imaging in hepatocellular carcinoma.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Dec 13, 2024
BACKGROUND: Hepatocellular carcinoma (HCC) exhibits an exceptional intratumoral heterogeneity that might influence diagnosis and outcome. Advances in digital microscopy and artificial intelligence (AI) may improve the HCC identification of liver canc...
Cell Nucleus Carcinoma, Hepatocellular Artificial Intelligence Microscopy, Confocal Machine Learning Deep Learning Liver Neoplasms Algorithms Humans
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AER-Net: Attention-Enhanced Residual Refinement Network for Nuclei Segmentation and Classification in Histology Images.

Sensors (Basel, Switzerland) Nov 11, 2024
The acurate segmentation and classification of nuclei in histological images are crucial for the diagnosis and treatment of colorectal cancer. However, the aggregation of nuclei and intra-class variability in histology images present significant chal...
Deep Learning Algorithms Humans Cell Nucleus Image Processing, Computer-Assisted Neural Networks, Computer Colorectal Neoplasms
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A survey on cell nuclei instance segmentation and classification: Leveraging context and attention.

Medical image analysis Oct 5, 2024
Nuclear-derived morphological features and biomarkers provide relevant insights regarding the tumour microenvironment, while also allowing diagnosis and prognosis in specific cancer types. However, manually annotating nuclei from the gigapixel Haemat...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Cell Nucleus Algorithms Image Processing, Computer-Assisted
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