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Cell Nucleus

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Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis.

Scientific reports
Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of alterations in mechanical propert...

Towards semantic-driven high-content image analysis: an operational instantiation for mitosis detection in digital histopathology.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study concerns a novel symbolic cognitive vision framework emerged from the Cognitive Microscopy (MICO(1)) initiative. MICO aims at supporting the evolution towards digital pathology, by studying cognitive clinical-compliant protocols involving ...

Does artificial intelligence redefine nuclear-to-cytoplasmic ratio threshold for diagnosing high-grade urothelial carcinoma?

Cancer cytopathology
BACKGROUND: The Paris System (TPS) introduced standardized nuclear-to-cytoplasmic (N/C) ratio thresholds for urine cytology to improve high-grade urothelial carcinoma (HGUC) detection, but these criteria remain subjective. This study used AIxURO, an ...

Deep generative model for protein subcellular localization prediction.

Briefings in bioinformatics
Protein sequence not only determines its structure but also provides important clues of its subcellular localization. Although a series of artificial intelligence models have been reported to predict protein subcellular localization, most of them pro...

Quantitative analysis of the dexamethasone side effect on human-derived young and aged skeletal muscle by myotube and nuclei segmentation using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Skeletal muscle cells (skMCs) combine together to create long, multi-nucleated structures called myotubes. By studying the size, length, and number of nuclei in these myotubes, we can gain a deeper understanding of skeletal muscle develop...

A CNN-GNN Approach for Polarity Vectors Prediction in 3D Microscopy Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The polarity between nuclei and Golgi is an important aspect of cellular division, migration and signaling. For example, nucleus-Golgi polarity significantly impacts angiogenesis, the physiological process in which new blood vessels develop from pre-...

Effect of learning parameters on the performance of the U-Net architecture for cell nuclei segmentation from microscopic cell images.

Microscopy (Oxford, England)
Nuclei segmentation of cells is the preliminary and essential step of pathological image analysis. However, robust and accurate cell nuclei segmentation is challenging due to the enormous variability of staining, cell sizes, morphologies, cell adhesi...

Transfer Learning Approach and Nucleus Segmentation with MedCLNet Colon Cancer Database.

Journal of digital imaging
Machine learning has been recently used especially in the medical field. In the diagnosis of serious diseases such as cancer, deep learning techniques can be used to reduce the workload of experts and to produce quick solutions. The nuclei found in t...

Usability of deep learning pipelines for 3D nuclei identification with Stardist and Cellpose.

Cells & development
Segmentation of 3D images to identify cells and their molecular outputs can be difficult and tedious. Machine learning algorithms provide a promising alternative to manual analysis as emerging 3D image processing technology can save considerable time...

Detecting and Classifying Nuclei Using Multi-Scale Fully Convolutional Network.

Journal of computational biology : a journal of computational molecular cell biology
The detection and classification of nuclei play an important role in the histopathological analysis. It aims to find out the distribution of nuclei in the histopathology images for the next step of analysis and research. However, it is very challengi...