AIMC Topic: Cell Nucleus

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Enhancing frozen histological section images using permanent-section-guided deep learning with nuclei attention.

Scientific reports Aug 20, 2025
In histological pathology, frozen sections are often used for rapid diagnosis during surgeries, as they can be produced within minutes. However, they suffer from artifacts and often lack crucial diagnostic details, particularly within the cell nuclei...
Image Processing, Computer-Assisted Cell Nucleus Frozen Sections Humans Deep Learning
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Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform.

PloS one Jul 10, 2025
Accurate nuclei segmentation and classification in histology images are critical for cancer detection but remain challenging due to color inconsistency, blurry boundaries, and overlapping nuclei. Manual segmentation is time-consuming and labor-intens...
Image Processing, Computer-Assisted Cell Nucleus Federated Learning Neoplasms Deep Learning Humans Algorithms
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Nuclear morphometrics coupled with machine learning identifies dynamic states of senescence across age.

Nature communications Jul 7, 2025
Cellular senescence is an irreversible state of cell cycle arrest with a complex role in tissue repair, aging, and disease. However, inconsistencies in identifying cellular senescence have led to varying conclusions about their functional significanc...
Machine Learning Female Animals Humans Mice Cellular Senescence Muscle, Skeletal Cell Nucleus Cartilage, Articular Male Aging Single-Cell Analysis
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Clustering cell nuclei on microgrooves for disease diagnosis using deep learning.

Scientific reports Jul 2, 2025
Various diseases including laminopathies and certain types of cancer are associated with abnormal nuclear mechanical properties that influence cellular and nuclear deformations in complex environments. Recently, microgroove substrates designed to mim...
Mutation Myoblasts Cell Nucleus Image Processing, Computer-Assisted Cluster Analysis Lamin Type A Humans Deep Learning
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Machine learning to detect melanoma exploiting nuclei morphology and Spatial organization.

Scientific reports Jul 1, 2025
Cutaneous melanoma is one of the most lethal forms of skin cancer, and its incidence is increasing globally. Its diagnosis typically relies on manual histopathological examination, a process that is both complex and time consuming. In this study, we ...
Skin Neoplasms Image Processing, Computer-Assisted Cell Nucleus Humans Machine Learning Melanoma
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Quantitative benchmarking of nuclear segmentation algorithms in multiplexed immunofluorescence imaging for translational studies.

Communications biology May 30, 2025
Multiplexed imaging techniques require identifying different cell types in the tissue. To utilize their potential for cellular and molecular analysis, high throughput and accurate analytical approaches are needed in parsing vast amounts of data, part...
Humans Algorithms Benchmarking Translational Research, Biomedical Image Processing, Computer-Assisted Cell Nucleus Fluorescent Antibody Technique
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The Role of Hydrogen Sulfide in the Localization and Structural-Functional Organization of p53 Following Traumatic Brain Injury: Development of a YOLO Model for Detection and Quantification of Apoptotic Nuclei.

International journal of molecular sciences May 24, 2025
Traumatic brain injury (TBI) triggers a cascade of molecular and cellular disturbances, including apoptosis, inflammation, and destabilization of neuronal connections. The transcription factor p53 plays a pivotal role in regulating cell fate followin...
Animals Tumor Suppressor Protein p53 Cell Nucleus Brain Injuries, Traumatic Hydrogen Sulfide Disease Models, Animal Male Apoptosis Rats Astrocytes Neurons
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MLDA-Net: Multi-Level Deep Aggregation Network for 3D Nuclei Instance Segmentation.

IEEE journal of biomedical and health informatics May 6, 2025
Segmentation of cell nuclei from three-dimensional (3D) volumetric fluorescence microscopy images is crucial for biological and clinical analyses. In recent years, convolutional neural networks have become the reliable 3D medical image segmentation s...
Microscopy, Fluorescence Cell Nucleus Deep Learning Imaging, Three-Dimensional Neural Networks, Computer Algorithms Humans
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Predicting cell cycle stage from 3D single-cell nuclear-stained images.

Life science alliance Apr 3, 2025
The cell cycle governs the proliferation of all eukaryotic cells. Profiling cell cycle dynamics is therefore central to basic and biomedical research. However, current approaches to cell cycle profiling involve complex interventions that may confound...
Cell Nucleus Cell Cycle Single-Cell Analysis Imaging, Three-Dimensional Support Vector Machine Microscopy, Fluorescence Image Processing, Computer-Assisted Humans Neural Networks, Computer Machine Learning
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Advancements in automated nuclei segmentation for histopathology using you only look once-driven approaches: A systematic review.

Computers in biology and medicine Mar 25, 2025
Histopathology image analysis plays a pivotal role in disease diagnosis and treatment planning, relying heavily on accurate nuclei segmentation for extracting vital cellular information. In recent years, artificial intelligence (AI) and in particular...
Image Interpretation, Computer-Assisted Cell Nucleus Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer
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