AIMC Topic: Cell Nucleus

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Multifunctional aggregation network of cell nuclei segmentation aiming histopathological diagnosis assistance: A new MA-Net construction.

PloS one Sep 6, 2024
Automated diagnostic systems can enhance the accuracy and efficiency of pathological diagnoses, nuclear segmentation plays a crucial role in computer-aided diagnosis systems for histopathology. However, achieving accurate nuclear segmentation is chal...
Image Processing, Computer-Assisted Cell Nucleus Algorithms Diagnosis, Computer-Assisted Deep Learning Humans Neural Networks, Computer
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Structure Embedded Nucleus Classification for Histopathology Images.

IEEE transactions on medical imaging Sep 3, 2024
Nuclei classification provides valuable information for histopathology image analysis. However, the large variations in the appearance of different nuclei types cause difficulties in identifying nuclei. Most neural network based methods are affected ...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Cell Nucleus Histocytochemistry Algorithms Image Processing, Computer-Assisted
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UNSEG: unsupervised segmentation of cells and their nuclei in complex tissue samples.

Communications biology Aug 30, 2024
Multiplexed imaging technologies have made it possible to interrogate complex tissue microenvironments at sub-cellular resolution within their native spatial context. However, proper quantification of this complexity requires the ability to easily an...
Unsupervised Machine Learning Bayes Theorem Cell Nucleus Deep Learning Image Processing, Computer-Assisted Humans Algorithms
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Convolutional neural network-based regression analysis to predict subnuclear chromatin organization from two-dimensional optical scattering signals.

Journal of biomedical optics Aug 28, 2024
SIGNIFICANCE: Azimuth-resolved optical scattering signals obtained from cell nuclei are sensitive to changes in their internal refractive index profile. These two-dimensional signals can therefore offer significant insights into chromatin organizatio...
Machine Learning Algorithms Regression Analysis Humans Neural Networks, Computer Refractometry Chromatin Cell Nucleus Scattering, Radiation
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Utilizing convolutional neural networks for discriminating cancer and stromal cells in three-dimensional cell culture images with nuclei counterstain.

Journal of biomedical optics Aug 24, 2024
SIGNIFICANCE: Accurate cell segmentation and classification in three-dimensional (3D) images are vital for studying live cell behavior and drug responses in 3D tissue culture. Evaluating diverse cell populations in 3D cell culture over time necessita...
Spheroids, Cellular Cell Culture Techniques, Three Dimensional Stromal Cells Cell Nucleus Humans Neural Networks, Computer Neoplasms Image Processing, Computer-Assisted Microscopy, Confocal Fibroblasts Cell Line, Tumor Imaging, Three-Dimensional
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aiSEGcell: User-friendly deep learning-based segmentation of nuclei in transmitted light images.

PLoS computational biology Aug 23, 2024
Segmentation is required to quantify cellular structures in microscopic images. This typically requires their fluorescent labeling. Convolutional neural networks (CNNs) can detect these structures also in only transmitted light images. This eliminate...
Cell Nucleus Mice Computational Biology Neural Networks, Computer Software Deep Learning Image Processing, Computer-Assisted Animals Humans
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An Automated Framework for Histopathological Nucleus Segmentation With Deep Attention Integrated Networks.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2024
Clinical management and accurate disease diagnosis are evolving from qualitative stage to the quantitative stage, particularly at the cellular level. However, the manual process of histopathological analysis is lab-intensive and time-consuming. Meanw...
Image Interpretation, Computer-Assisted Cell Nucleus Histocytochemistry Humans Algorithms Deep Learning
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A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context.

Development (Cambridge, England) Jul 18, 2024
We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We have developed an approach for ground truth generation and iterative training of 3D nuclear segmentation...
Cell Nucleus Arabidopsis Algorithms Animals Imaging, Three-Dimensional Image Processing, Computer-Assisted Deep Learning Software
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A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting.

IEEE transactions on neural networks and learning systems Jun 3, 2024
The detection and segmentation of stained cells and nuclei are essential prerequisites for subsequent quantitative research for many diseases. Recently, deep learning has shown strong performance in many computer vision problems, including solutions ...
Neural Networks, Computer Algorithms Neoplasms Deep Learning Animals Humans Microscopy Cell Nucleus Image Processing, Computer-Assisted Alzheimer Disease
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Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology.

Computers in biology and medicine May 14, 2024
Segmentation and classification of large numbers of instances, such as cell nuclei, are crucial tasks in digital pathology for accurate diagnosis. However, the availability of high-quality datasets for deep learning methods is often limited due to th...
Image Processing, Computer-Assisted Cell Nucleus Neural Networks, Computer Deep Learning Humans
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