AIMC Topic: Microscopy

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Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning.

Lab on a chip Sep 14, 2021
Particle agglutination assays are widely adopted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic particles are mixed with a test sample that potentially contains the target antigen, as a result of whic...
Point-of-Care Testing Microscopy Holography Agglutination Humans Deep Learning
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Misic, a general deep learning-based method for the high-throughput cell segmentation of complex bacterial communities.

eLife Sep 9, 2021
Studies of bacterial communities, biofilms and microbiomes, are multiplying due to their impact on health and ecology. Live imaging of microbial communities requires new tools for the robust identification of bacterial cells in dense and often inter-...
Microbiota Microscopy High-Throughput Screening Assays Deep Learning Bacterial Physiological Phenomena Biofilms Species Specificity Models, Biological
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Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.

European journal of cancer (Oxford, England : 1990) Sep 8, 2021
BACKGROUND: Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinic...
Skin Neoplasms Dermoscopy Reproducibility of Results Humans Neural Networks, Computer Melanoma Predictive Value of Tests Biopsy Pathologists Dermatologists Diagnosis, Computer-Assisted Deep Learning Clinical Competence Microscopy Image Interpretation, Computer-Assisted Automation
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Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection.

PLoS neglected tropical diseases Sep 7, 2021
Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is the diagnosis method recommended by the World Health Organization (WHO) although it often presents a d...
Humans Telemedicine Microscopy Trichuris Algorithms Animals Trichuriasis Deep Learning
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Helminth egg analysis platform (HEAP): An opened platform for microscopic helminth egg identification and quantification based on the integration of deep learning architectures.

Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi Sep 2, 2021
BACKGROUND: Millions of people throughout the world suffer from parasite infections. Traditionally, technicians use manual eye inspection of microscopic specimens to perform a parasite examination. However, manual operations have limitations that hin...
Neural Networks, Computer Algorithms Animals Deep Learning Microscopy Helminths Humans
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Automated detection of superficial fungal infections from microscopic images through a regional convolutional neural network.

PloS one Aug 17, 2021
Direct microscopic examination with potassium hydroxide is generally used as a screening method for diagnosing superficial fungal infections. Although this type of examination is faster than other diagnostic methods, it can still be time-consuming to...
Datasets as Topic Skin Hyphae Nails Humans Dermatomycoses Hydroxides Microscopy Potassium Compounds Image Interpretation, Computer-Assisted Deep Learning Arthrodermataceae ROC Curve
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Robust deep learning optical autofocus system applied to automated multiwell plate single molecule localization microscopy.

Journal of microscopy Aug 13, 2021
We presenta robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, for ex...
Microscopy Single Molecule Imaging Machine Learning Deep Learning
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Vesseg: An Open-Source Tool for Deep Learning-Based Atherosclerotic Plaque Quantification in Histopathology Images-Brief Report.

Arteriosclerosis, thrombosis, and vascular biology Aug 12, 2021
Objective: Manual plaque segmentation in microscopy images is a time-consuming process in atherosclerosis research and potentially subject to unacceptable user-to-user variability and observer bias. We address this by releasing Vesseg a tool that inc...
Software Female Reproducibility of Results Animals Arteries Predictive Value of Tests Male Atherosclerosis Severity of Illness Index Staining and Labeling Microscopy Disease Models, Animal Diagnosis, Computer-Assisted Mice, Knockout, ApoE Mice, Inbred C57BL Deep Learning Plaque, Atherosclerotic Image Interpretation, Computer-Assisted Mice Vascular Remodeling
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Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Aug 10, 2021
Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the ...
Animals Deep Learning Image Processing, Computer-Assisted Algorithms Cells, Cultured Mice Holography Microscopy Tissue Culture Techniques Intestine, Small Organoids
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Automatic cell counting from stimulated Raman imaging using deep learning.

PloS one Jul 21, 2021
In this paper, we propose an automatic cell counting framework for stimulated Raman scattering (SRS) images, which can assist tumor tissue characteristic analysis, cancer diagnosis, and surgery planning processes. SRS microscopy has promoted tumor di...
Image Processing, Computer-Assisted Spectrum Analysis, Raman Microscopy Humans Brain Neoplasms Deep Learning
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