AIMC Topic: Cell Nucleus

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Cyto R-CNN and CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images.

Computer methods and programs in biomedicine May 11, 2024
BACKGROUND AND OBJECTIVE: Cell segmentation in bright-field histological slides is a crucial topic in medical image analysis. Having access to accurate segmentation allows researchers to examine the relationship between cellular morphology and clinic...
Carcinoma, Squamous Cell Reproducibility of Results Neural Networks, Computer Algorithms Head and Neck Neoplasms Cell Nucleus Cytoplasm Humans Image Processing, Computer-Assisted Squamous Cell Carcinoma of Head and Neck
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Comprehensive data analysis of white blood cells with classification and segmentation by using deep learning approaches.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Apr 2, 2024
Deep learning approaches have frequently been used in the classification and segmentation of human peripheral blood cells. The common feature of previous studies was that they used more than one dataset, but used them separately. No study has been fo...
Humans Leukocytes Cell Nucleus Cytoplasm Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Data Analysis
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CellViT: Vision Transformers for precise cell segmentation and classification.

Medical image analysis Mar 16, 2024
Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications. However, it is a challenging task due to nuclei variances in staining and size, overlapp...
Staining and Labeling Cell Nucleus Eosine Yellowish-(YS) Hematoxylin Neural Networks, Computer Image Processing, Computer-Assisted Humans
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NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.

Scientific data Mar 14, 2024
In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for this task, supervised deep learning (DL) methods have shown superior s...
Animals Image Processing, Computer-Assisted Humans Machine Learning Cell Nucleus Mice Staining and Labeling
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Fluorescent Neuronal Cells v2: multi-task, multi-format annotations for deep learning in microscopy.

Scientific data Feb 10, 2024
Fluorescent Neuronal Cells v2 is a collection of fluorescence microscopy images and the corresponding ground-truth annotations, designed to foster innovative research in the domains of Life Sciences and Deep Learning. This dataset encompasses three i...
Cell Nucleus Deep Learning Microscopy, Fluorescence Image Processing, Computer-Assisted Neurons
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Comparison between a deep-learning and a pixel-based approach for the automated quantification of HIV target cells in foreskin tissue.

Scientific reports Jan 23, 2024
The availability of target cells expressing the HIV receptors CD4 and CCR5 in genital tissue is a critical determinant of HIV susceptibility during sexual transmission. Quantification of immune cells in genital tissue is therefore an important outcom...
Humans Male Foreskin Cell Count Cell Nucleus Deep Learning HIV Infections
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Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images.

Nature communications Dec 11, 2023
Recent advancements in tissue imaging techniques have facilitated the visualization and identification of various cell types within physiological and pathological contexts. Despite the emergence of cell-cell interaction studies, there is a lack of me...
Humans Cell Communication Deep Learning Cell Nucleus Lung Neoplasms
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Deep Learning-Based H-Score Quantification of Immunohistochemistry-Stained Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Dec 1, 2023
Immunohistochemistry (IHC) is a well-established and commonly used staining method for clinical diagnosis and biomedical research. In most IHC images, the target protein is conjugated with a specific antibody and stained using diaminobenzidine (DAB),...
Immunohistochemistry Hematoxylin Deep Learning Cell Nucleus Humans Algorithms
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Nuclei instance segmentation from histopathology images using Bayesian dropout based deep learning.

BMC medical imaging Oct 19, 2023
BACKGROUND: The deterministic deep learning models have achieved state-of-the-art performance in various medical image analysis tasks, including nuclei segmentation from histopathology images. The deterministic models focus on improving the model pre...
Cell Nucleus Humans Image Processing, Computer-Assisted Neural Networks, Computer Bayes Theorem Deep Learning
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Plantorganelle Hunter is an effective deep-learning-based method for plant organelle phenotyping in electron microscopy.

Nature plants Sep 25, 2023
Accurate delineation of plant cell organelles from electron microscope images is essential for understanding subcellular behaviour and function. Here we develop a deep-learning pipeline, called the organelle segmentation network (OrgSegNet), for pixe...
Cell Nucleus Chloroplasts Deep Learning Microscopy, Electron Mitochondria
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