AIMC Topic: Microscopy
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Deep learning-based automated detection and multiclass classification of soil-transmitted helminths and Schistosoma mansoni eggs in fecal smear images.
Scientific reports
Jul 1, 2025
In this work, we developed an automated system for the detection and classification of soil-transmitted helminths (STH) and Schistosoma (S.) mansoni eggs in microscopic images of fecal smears. We assembled an STH and S. mansoni dataset comprising ove...
Deep-learning-based automated prediction of mouse seminiferous tubule stage by using bright-field microscopy.
Scientific reports
Jul 1, 2025
Infertility is a global issue, and approximately 50% of cases are due to male factors, with defective spermatogenesis being the main one. For studies of spermatogenesis, evaluating the seminiferous tubule stage is essential. However, current evaluati...
Spatial patterns of hepatocyte glucose flux revealed by stable isotope tracing and multi-scale microscopy.
Nature communications
Jul 1, 2025
Metabolic homeostasis requires engagement of catabolic and anabolic pathways consuming nutrients that generate and consume energy and biomass. Our current understanding of cell homeostasis and metabolism, including how cells utilize nutrients, comes ...
AI-supported versus manual microscopy of Kato-Katz smears for diagnosis of soil-transmitted helminth infections in a primary healthcare setting.
Scientific reports
Jun 27, 2025
Soil-transmitted helminths primarily comprise Ascaris lumbricoides, Trichuris trichiura, and hookworms, infecting more than 600 million people globally, particularly in underserved communities. Manual microscopy of Kato-Katz thick smears is a widely ...
Systematic review of generative adversarial networks (GANs) in cell microscopy: Trends, practices, and impact on image augmentation.
PloS one
Jun 24, 2025
Cell microscopy is the main tool that allows researchers to study microorganisms and plays a key role in observing and understanding the morphology, interactions, and development of microorganisms. However, there exist limitations in both the techniq...
Visualizing nuclear pore complex plasticity with pan-expansion microscopy.
The Journal of cell biology
Jun 12, 2025
The exploration of cell-type and environmentally responsive nuclear pore complex (NPC) plasticity requires new, accessible tools. Using pan-expansion microscopy (pan-ExM), NPCs were identified by machine learning-facilitated segmentation. They exhibi...
Application of ConvNeXt with transfer learning and data augmentation for malaria parasite detection in resource-limited settings using microscopic images.
PloS one
Jun 4, 2025
Malaria continues to be a severe health problem across the globe, especially within resource-limited areas which lack both skilled diagnostic personnel and diagnostic equipment. This study investigates the use of deep learning diagnosis for malaria t...
A Benchmark for Virus Infection Reporter Virtual Staining in Fluorescence and Brightfield Microscopy.
Scientific data
May 28, 2025
Detecting virus-infected cells in light microscopy requires a reporter signal commonly achieved by immunohistochemistry or genetic engineering. While classification-based machine learning approaches to the detection of virus-infected cells have been ...
Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells.
PLoS computational biology
May 23, 2025
Deep learning-based methods for identifying and tracking cells within microscopy images have revolutionized the speed and throughput of data analysis. These methods for analyzing biological and medical data have capitalized on advances from the broad...
A Complete Transfer Learning-Based Pipeline for Discriminating Between Select Pathogenic Yeasts from Microscopy Photographs.
Pathogens (Basel, Switzerland)
May 21, 2025
Pathogenic yeasts are an increasing concern in healthcare, with species like often displaying drug resistance and causing high mortality in immunocompromised patients. The need for rapid and accessible diagnostic methods for accurate yeast identific...
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