AIMC Topic: Microscopy

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Near-zero photon bioimaging by fusing deep learning and ultralow-light microscopy.

Proceedings of the National Academy of Sciences of the United States of America May 27, 2025
Enhancing the reliability and reproducibility of optical microscopy by reducing specimen irradiance continues to be an important biotechnology target. As irradiance levels are reduced, however, the particle nature of light is heightened, giving rise ...
Humans Deep Learning Microscopy Photons Image Processing, Computer-Assisted Microscopy, Fluorescence
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Single-shot reconstruction of three-dimensional morphology of biological cells in digital holographic microscopy using a physics-driven neural network.

Nature communications May 24, 2025
Recent advances in deep learning-based image reconstruction techniques have led to significant progress in phase retrieval using digital in-line holographic microscopy (DIHM). However, existing phase retrieval methods have technical limitations in 3D...
Quantitative Phase Imaging Microscopy Holography Humans Imaging, Three-Dimensional Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Algorithms
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Intelligent System for Automated Spheroid Segmentation Using Machine Learning.

Studies in health technology and informatics May 15, 2025
Image segmentation is a crucial task of medical image processing, including the analysis of multicellular tumour spheroids (MTSs), a common in vitro model used in cancer research for drug screening. Accurate segmentation of MTSs images allows the ext...
Pattern Recognition, Automated Image Processing, Computer-Assisted Humans Microscopy Machine Learning Spheroids, Cellular Artificial Intelligence Intelligent Systems
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Measuring Cell Dimensions in Fission Yeast Using Machine Learning.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
In fission yeast (Schizosaccharomyces pombe), cell length is a crucial indicator of cell cycle progression. Microscopy screens that examine the effect of agents or genotypes suspected of altering genomic or metabolic stability and thus cell size are ...
Image Processing, Computer-Assisted DNA Damage Microscopy Machine Learning Schizosaccharomyces Cell Cycle Genomic Instability
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Evaluation of alarm notification of artificial intelligence in automated analyzer detection of parasites.

Medicine Sep 27, 2024
To evaluate the alarm notification of artificial intelligence in detecting parasites on the KU-F40 Fully Automatic Feces Analyzer and provide a reference for clinical diagnosis in parasite diseases. A total of 1030 fecal specimens from patients in ou...
Parasitic Diseases Child, Preschool Child Microscopy Parasites Feces Male Middle Aged Humans Adolescent Artificial Intelligence Adult Aged Sensitivity and Specificity Young Adult Female
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[Opportunities and expectations brought by artificial intelligence assisted peripheral blood cell morphology examination].

Zhonghua yi xue za zhi Aug 27, 2024
The morphological examination of blood cells under manual microscopes is a classic method, but the obvious shortcomings limit the extensive development of peripheral blood cell morphological examination. By using the manual microscope method, it is d...
Blood Cells Humans Artificial Intelligence Microscopy
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Next generation mycological diagnosis: Artificial intelligence-based classifier of the presence of Malassezia yeasts in tape strip samples.

Mycoses Aug 1, 2024
BACKGROUND: Malassezia yeasts are almost universally present on human skin worldwide. While they can cause diseases such as pityriasis versicolor, their implication in skin homeostasis and pathophysiology of other dermatoses is still unclear. Their a...
Algorithms Humans Artificial Intelligence Microscopy Sensitivity and Specificity Image Processing, Computer-Assisted Dermatomycoses Skin Malassezia
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Automating Wood Species Detection and Classification in Microscopic Images of Fibrous Materials with Deep Learning.

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada Jul 4, 2024
We have developed a methodology for the systematic generation of a large image dataset of macerated wood references, which we used to generate image data for nine hardwood genera. This is the basis for a substantial approach to automate, for the firs...
Microscopy Wood Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted
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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 Jul 1, 2024
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-...
Retina Microscopy Animals Golgi Apparatus Neural Networks, Computer Imaging, Three-Dimensional Cell Polarity Algorithms Mice Cell Nucleus
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Deep Learning Method for Estimating Germ-layer Regions of Early Differentiated Human Induced Pluripotent Stem Cells on Micropattern Using Bright-field Microscopy Image.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Live cell staining is expensive and may bring potential safety issues in downstream clinical applications, bright-field images rather than staining images should be more suitable to reveal time-series changes of differentiating hiPSCs (human induced ...
Image Processing, Computer-Assisted Cell Differentiation Microscopy Humans Deep Learning Induced Pluripotent Stem Cells Germ Layers
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