AIMC Topic: Microscopy

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Harnessing artificial intelligence microscopy to improve diagnostics for soil-transmitted helminthiasis and schistosomiasis: a review of recent advances and future pathways.

Current opinion in infectious diseases Aug 2, 2024
PURPOSE OF REVIEW: This opinion piece aims to explore the transformative potential of integrating artificial intelligence with digital microscopy to enhance diagnostics for soil-transmitted helminthiasis (STH) and schistosomiasis (SCH), two pervasive...
Humans Artificial Intelligence Soil Schistosomiasis Helminthiasis Neglected Diseases Animals Microscopy
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A proposal for cut marks classification using machine learning: Serrated vs. non-serrated, single vs. double-beveled knives.

Journal of forensic sciences Jul 25, 2024
In tool mark identification, there is still a lack of characteristics and methodologies standardization used to analyze and describe sharp force trauma marks on skeletal remains. This study presents a classification method for cut marks on human bone...
Machine Learning Animals Swine Ribs Wounds, Stab Microscopy Models, Animal Logistic Models Weapons Equipment Design
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Cytopathic Effect Detection and Clonal Selection using Deep Learning.

Pharmaceutical research Jul 24, 2024
PURPOSE: In biotechnology, microscopic cell imaging is often used to identify and analyze cell morphology and cell state for a variety of applications. For example, microscopy can be used to detect the presence of cytopathic effects (CPE) in cell cul...
Cytopathogenic Effect, Viral Cell Line Microscopy Deep Learning Image Processing, Computer-Assisted Humans Algorithms Animals Neural Networks, Computer
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Evaluating artificial intelligence-enhanced digital urine cytology for bladder cancer diagnosis.

Cancer cytopathology Jul 14, 2024
BACKGROUND: This study evaluated the diagnostic effectiveness of the AIxURO platform, an artificial intelligence-based tool, to support urine cytology for bladder cancer management, which typically requires experienced cytopathologists and substantia...
Urinary Bladder Neoplasms Cytodiagnosis Microscopy Sensitivity and Specificity Male Carcinoma, Transitional Cell Urine Humans Female Aged Artificial Intelligence
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Reconstructing Cancellous Bone From Down-Sampled Optical-Resolution Photoacoustic Microscopy Images With Deep Learning.

Ultrasound in medicine & biology Jul 7, 2024
OBJECTIVE: Bone diseases deteriorate the microstructure of bone tissue. Optical-resolution photoacoustic microscopy (OR-PAM) enables high spatial resolution of imaging bone tissues. However, the spatiotemporal trade-off limits the application of OR-P...
Animals Deep Learning Cattle Signal-To-Noise Ratio Image Processing, Computer-Assisted Photoacoustic Techniques Microscopy Cancellous Bone
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Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.

Analytical chemistry Jul 2, 2024
Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recentl...
Microscopy Animals Electric Impedance Deep Learning Electrochemical Techniques Action Potentials Neurons
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Background removal for debiasing computer-aided cytological diagnosis.

International journal of computer assisted radiology and surgery Jun 25, 2024
To address the background-bias problem in computer-aided cytology caused by microscopic slide deterioration, this article proposes a deep learning approach for cell segmentation and background removal without requiring cell annotation. A U-Net-based ...
Image Interpretation, Computer-Assisted Cytodiagnosis Microscopy Diagnosis, Computer-Assisted Humans Deep Learning
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An automated in vitro wound healing microscopy image analysis approach utilizing U-net-based deep learning methodology.

BMC medical imaging Jun 25, 2024
BACKGROUND: The assessment of in vitro wound healing images is critical for determining the efficacy of the therapy-of-interest that may influence the wound healing process. Existing methods suffer significant limitations, such as user dependency, ti...
Humans Neural Networks, Computer Wound Healing Deep Learning Microscopy Image Processing, Computer-Assisted
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Cross-Modal Graph Contrastive Learning with Cellular Images.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jun 21, 2024
Constructing discriminative representations of molecules lies at the core of a number of domains such as drug discovery, chemistry, and medicine. State-of-the-art methods employ graph neural networks and self-supervised learning (SSL) to learn unlabe...
Image Processing, Computer-Assisted Microscopy Machine Learning Humans Algorithms Neural Networks, Computer
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DeepLeish: a deep learning based support system for the detection of Leishmaniasis parasite from Giemsa-stained microscope images.

BMC medical imaging Jun 18, 2024
BACKGROUND: Leishmaniasis is a vector-born neglected parasitic disease belonging to the genus Leishmania. Out of the 30 Leishmania species, 21 species cause human infection that affect the skin and the internal organs. Around, 700,000 to 1,000,000 of...
Azure Stains Leishmaniasis Leishmania Deep Learning Microscopy Humans
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