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Updated: Feb 13, 2026
09:33
Automated Slide Scanning and Segmentation in Fluorescently-labeled Tissues Using a Widefield High-content Analysis System
Published on: May 3, 2018
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Continuous stacking computational approach based automated microscope slide scanner
Swetha Murali1, Jayesh Vasudeva Adhikari1, Veerendra Kalyan Jagannadh1
1Department of Instrumentation and Applied Physics, Indian Institute of Science, C.V. Raman Road, Bangalore, Karnataka 560012, India.
The Review of Scientific Instruments
|March 3, 2018
Summary
A new automated microscope slide scanner, built affordably, generates high-quality digital pathology images. This technology enables cost-effective malaria diagnosis and quantitative parasitemia estimation in endemic regions.
Area of Science:
- Digital Pathology
- Medical Imaging
- Biomedical Engineering
Background:
- Automated whole slide image acquisition is crucial for digital pathology's widespread use but remains a challenge.
- Existing solutions are often costly, limiting accessibility in resource-limited settings.
Purpose of the Study:
- To develop a cost-effective, automated microscope slide scanner prototype.
- To demonstrate its capability for clinical diagnostic testing, specifically for malaria detection.
Main Methods:
- Utilized a computation-augmented approach with inexpensive, off-the-shelf optical components and motors.
- Developed a prototype automated microscope slide scanner.
- Applied image processing techniques to analyze malaria-infected blood smear images.
Main Results:
- Successfully generated good quality digital images of malaria-infected blood smears.
- Developed a method for identifying and counting malaria-infected red blood cells.
- Enabled quantitative estimation of parasitemia levels from acquired images.
Conclusions:
- The developed prototype offers a cost-effective solution for automated slide scanning.
- It has demonstrated applicability for clinical diagnostic testing, including malaria detection.
- This technology can facilitate the deployment of slide-based cyto-diagnostic testing in endemic areas.
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