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The dry lab microscopist or prompt microscopist: do we need them?
Biophys Rev
December 2024
School of Computer Science (Biomedical & Multimedia Information Technology), Faculty of Engineering, The University of Sydney, Sydney, NSW 2006 Australia.
In modern biological microscopy, the explosion of data volume and complexity highlights the urgent need for specialised data management support roles. While traditional microscopy focuses on visual data presentation, the rapid increase in big data acquisition and data mining demands advanced handling and analysis. This gap underscores the need for "dry lab microscopists" or data experts skilled in microscopy data management, software interoperability, and AI-driven solutions.
View Article and Find Full Text PDFVariability of interobserver interpretation of selected helminth ova in the development of a training image set.
Int Health
January 2025
Neglected Tropical Diseases Study Group, National Institutes of Health, University of the Philippines Manila, Manila, Philippines.
Background: Diagnosis of soil-transmitted helminthiasis and schistosomiasis for surveillance relies on microscopic detection of ova in Kato-Katz (KK) prepared slides. Artificial intelligence (AI)-based platforms for parasitic eggs may be developed using a robust image set with defined labels by reference microscopists. This study aimed to determine interobserver variability among reference microscopists in identifying parasite ova.
View Article and Find Full Text PDFMalaria parasite detection in Red Blood Cells with rouleaux formation morphology using YOLOv9.
Tissue Cell
December 2024
Department of Electronics and Computer Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor Bahru, Johor 81310 UTM, Malaysia.
Article Synopsis
- Malaria is common in poor areas and often shows comorbidity with other infections that cause a specific Red Blood Cell deformity called rouleaux formation, which looks like stacked coins.
- The presence of this deformity is important for diagnosing other diseases and is reported by microscopists, especially in malaria patients.
- To enhance malaria diagnostics, a study created a blood smear dataset featuring RBCs with rouleaux formation infected by two malaria species and utilized YOLOv9s architecture to improve detection accuracy of malaria parasites and white blood cells.
Principle of TEM alignment using convolutional neural networks: Case study on condenser aperture alignment.
Ultramicroscopy
December 2024
CEMES-CNRS, 29 rue Jeanne Marvig, Toulouse, 31055, France.
The possibility of automatically aligning the transmission electron microscope (TEM) is explored using an approach based on artificial intelligence (AI). After presenting the general concept, we test the method on the first step of the alignment process which involves centering the condenser aperture. We propose using a convolutional neural network (CNN) that learns to predict the x and y-shifts needed to realign the aperture in one step.
View Article and Find Full Text PDFDevelopment of intelligent suite for malaria pathogen detection in microscopy images.
Sci Rep
October 2024
Intel Technology India Pvt. Ltd., Bengaluru, Karnataka, India.
Article Synopsis
- - The study introduces the Intelligent Suite, a software designed to automate the detection of malaria pathogens in blood smear microscope images, aiming to alleviate the shortage of expert microscopists in remote areas.
- - It features a user-friendly graphical interface utilizing the 'cvui' library and integrates with OpenVINO for model optimization, allowing deployment on various inference devices.
- - The Intelligent Suite employs a custom YOLO-mp-3l model, trained on the Darknet framework, to analyze thick smear images and provides functionalities for device selection, model parameter adjustments, and generating performance reports.
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