AIMC Topic: Cell Nucleus

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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...
Machine Learning Animals Humans Staining and Labeling Cell Nucleus Image Processing, Computer-Assisted Mice
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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 Image Processing, Computer-Assisted Microscopy, Fluorescence 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...
Deep Learning HIV Infections Humans Male Cell Nucleus Cell Count Foreskin
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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...
Cell Communication Cell Nucleus Deep Learning Lung Neoplasms Humans
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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...
Deep Learning Image Processing, Computer-Assisted Humans Bayes Theorem Neural Networks, Computer Cell Nucleus
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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...
Chloroplasts Cell Nucleus Microscopy, Electron Mitochondria Deep Learning
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Structure-based prediction of nucleic acid binding residues by merging deep learning- and template-based approaches.

PLoS computational biology Sep 6, 2023
Accurate prediction of nucleic binding residues is essential for the understanding of transcription and translation processes. Integration of feature- and template-based strategies could improve the prediction of these key residues in proteins. Never...
Algorithms Deep Learning Walking Cell Nucleus Nucleic Acids
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An artificial intelligence-based ecological index for prognostic evaluation of colorectal cancer.

BMC cancer Aug 17, 2023
BACKGROUND AND OBJECTIVE: In the tumor microenvironment (TME), the dynamic interaction between tumor cells and immune cells plays a critical role in predicting the prognosis of colorectal cancer. This study introduces a novel approach based on artifi...
Prognosis Colorectal Neoplasms Artificial Intelligence Hydrolases Tumor Microenvironment Humans Cell Nucleus
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Integrative deep learning analysis improves colon adenocarcinoma patient stratification at risk for mortality.

EBioMedicine Jul 25, 2023
BACKGROUND: Colorectal cancers are the fourth most diagnosed cancer and the second leading cancer in number of deaths. Many clinical variables, pathological features, and genomic signatures are associated with patient risk, but reliable patient strat...
Adenocarcinoma Deep Learning Humans Colonic Neoplasms Cell Nucleus Genomics
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