AIMC Topic: Microscopy

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Precise Pollen Grain Detection in Bright Field Microscopy Using Deep Learning Techniques.

Sensors (Basel, Switzerland) Aug 17, 2019
The determination of daily concentrations of atmospheric pollen is important in the medical and biological fields. Obtaining pollen concentrations is a complex and time-consuming task for specialized personnel. The automatic location of pollen grains...
Videotape Recording Deep Learning Microscopy Pollen Reproducibility of Results
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An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.

Nature medicine Aug 12, 2019
The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessments demonstrate considerable variability and many regions of the world lack access to trained pathol...
Microscopy Neoplasms Prostatic Neoplasms Neoplasm Staging Humans Artificial Intelligence Female Breast Neoplasms Male
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Deep learning-based color holographic microscopy.

Journal of biophotonics Aug 1, 2019
We report a framework based on a generative adversarial network that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated simultaneously by light at three different wavelengths. The trained network...
Humans Male Prostate Microscopy Holography Deep Learning Image Processing, Computer-Assisted Color
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Characterization of Nanoscale Organization of F-Actin in Morphologically Distinct Dendritic Spines Using Supervised Learning.

eNeuro Aug 1, 2019
The cytoarchitecture of a neuron is very important in defining morphology and ultrastructure. Although there is a wealth of information on the molecular components that make and regulate these ultrastructures, there is a dearth of understanding of ho...
Dendritic Spines Microscopy Hippocampus Actins Animals Male In Vitro Techniques Image Processing, Computer-Assisted Rats, Sprague-Dawley Supervised Machine Learning Female
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Artificial intelligence for microscopy: what you should know.

Biochemical Society transactions Jul 31, 2019
Artificial Intelligence based on Deep Learning (DL) is opening new horizons in biomedical research and promises to revolutionize the microscopy field. It is now transitioning from the hands of experts in computer sciences to biomedical researchers. H...
Microscopy Neural Networks, Computer Artificial Intelligence Algorithms
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Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images.

European journal of cancer (Oxford, England : 1990) Jul 18, 2019
BACKGROUND: The diagnosis of most cancers is made by a board-certified pathologist based on a tissue biopsy under the microscope. Recent research reveals a high discordance between individual pathologists. For melanoma, the literature reports on 25-2...
Reproducibility of Results Observer Variation Pathologists Diagnosis, Computer-Assisted Nevus Microscopy Humans Deep Learning Image Interpretation, Computer-Assisted Melanoma Diagnosis, Differential Skin Neoplasms Predictive Value of Tests Biopsy
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Identifying non-O157 Shiga toxin-producing Escherichia coli (STEC) using deep learning methods with hyperspectral microscope images.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 16, 2019
Non-O157 Shiga toxin-producing Escherichia coli (STEC) serogroups such as O26, O45, O103, O111, O121 and O145 often cause illness to people in the United States and the conventional identification of these "Big-Six" are complex. The label-free hypers...
Deep Learning Image Processing, Computer-Assisted Food Microbiology Foodborne Diseases Principal Component Analysis Shiga-Toxigenic Escherichia coli Humans Algorithms Microscopy Optical Imaging Bacterial Typing Techniques
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3D Neuron Reconstruction in Tangled Neuronal Image With Deep Networks.

IEEE transactions on medical imaging Jul 9, 2019
Digital reconstruction or tracing of 3D neuron is essential for understanding the brain functions. While existing automatic tracing algorithms work well for the clean neuronal image with a single neuron, they are not robust to trace the neuron surrou...
Humans Algorithms Imaging, Three-Dimensional Mice Neurons Brain Animals Deep Learning Microscopy Nerve Fibers
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AMC-Net: Asymmetric and multi-scale convolutional neural network for multi-label HPA classification.

Computer methods and programs in biomedicine Jul 9, 2019
BACKGROUND AND OBJECTIVES: The multi-label Human Protein Atlas (HPA) classification can yield a better understanding of human diseases and help doctors to enhance the automatic analysis of biomedical images. The existing automatic protein recognition...
Proteins Databases, Protein Microscopy, Fluorescence Phenotype Humans Pattern Recognition, Automated Microscopy Reproducibility of Results Neural Networks, Computer Cell Nucleus Probability Algorithms Image Processing, Computer-Assisted False Positive Reactions Microtubules
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Segmenting and tracking cell instances with cosine embeddings and recurrent hourglass networks.

Medical image analysis Jun 29, 2019
Differently to semantic segmentation, instance segmentation assigns unique labels to each individual instance of the same object class. In this work, we propose a novel recurrent fully convolutional network architecture for tracking such instance seg...
Datasets as Topic Muscle Fibers, Skeletal Cell Tracking Humans Image Processing, Computer-Assisted Neural Networks, Computer Microscopy Algorithms Video Recording
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