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Updated: Jun 30, 2026
08:05
Murine Model of Allergen Induced Asthma
Published on: May 14, 2012
Automatic quantification of histological studies in allergic asthma
Mónica Abella1, José Manuel Zubeldia, Laura Conejero
1Hospital Gregorio Marañón, Madrid, Spain.
Summary
This study introduces a new software tool for automatically quantifying cellular infiltrate in lung tissue images, crucial for evaluating allergic asthma therapies. The automated method achieves expert-level accuracy, enabling faster and more repeatable analysis of histological studies.
Area of Science:
- * Pulmonary Pathology and Computational Imaging
- * Allergic Asthma Research and Therapeutic Evaluation
Background:
- * Histological studies of lung tissue are vital for assessing allergic asthma treatments, often relying on manual quantification of cellular infiltrate.
- * Current manual methods are time-consuming and prone to variability, lacking automated software solutions.
Purpose of the Study:
- * To develop and validate a novel software tool for the automated quantification of cellular infiltrate in lung tissue images.
- * To provide a reliable, repeatable, and efficient method for analyzing histological data in allergic asthma research.
Main Methods:
- * Image segmentation using a texture analysis algorithm, classifying regions based on histogram and co-occurrence matrix parameters.
- * Development of three discriminant functions via stepwise discriminant analysis on a training set of 79 samples.
- * Validation using an independent test set of 251 manually labeled samples.
Main Results:
- * Achieved 96.8% correct classification accuracy on an independent test set.
- * Demonstrated good agreement between automated quantification and manual expert assessment through regression analysis.
- * The developed method is reliable, easy to implement, and comparable in accuracy to expert analysis.
Conclusions:
- * A robust automated method for quantifying cellular infiltrate in lung histology images has been successfully developed.
- * The software tool offers a significant advancement for allergic asthma research, enabling high-throughput and consistent analysis.
- * This automated approach enhances the efficiency and reliability of histological evaluations in preclinical studies.
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