Graduation Year

2025

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Environmental Analysis

Reader 1

Sarah Budischak

Reader 2

Elise Ferree

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Terms of Use for work posted in Scholarship@Claremont.

Abstract

Across the globe we have seen the continued decline of avian populations resulting in the loss of billions of breeding individuals with serious implications for the ecosystems they hold together. One mechanism for evaluating population health is stress which can be understood through white blood cell counts from blood smears. This study aims to develop a new method for counting white blood cells using QuPath, an open-access software that uses artificial intelligence for bioimage analysis. Additionally, this study aims to evaluate the accuracy and efficiency of QuPath in comparison to manual evaluation and what the pros and cons are of this new research method. A protocol was successfully developed to identify avian blood cells into groups of white blood cells, young and mature red blood cells, and smushed cells. Compared to a manual evaluation of the same slides, QuPath had a specificity value of 99.0% (± 0.5%) and a sensitivity value of 93.2% (± 2.7%), indicating high accuracy. Although the program was relatively accurate, it currently is not as time efficient as a manual evaluation of blood slides. On the other hand, one major positive is storing these images and their classifications digitally greatly increases the potential for collaboration, repeatability, and training across researchers. With increased training and streamlining of our methods, it is possible to greatly improve QuPath’s efficiency showing its great potential for future use.

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