Drexel University

College of Computing and Informatics

Digital Pathology and Eosinophil Detection

Humanitarian
Make use of machine learning to help pathologists identify the density of the eosinophil cells in digital slides of human nasal tissue.
    The Digital Pathology project aims to use computer neural networks in an effort to reduce the time-consuming activity of analyzing digital slides during diagnosis of Sinusitis. This project was initially started in 2018 as a Senior Design project and then improved upon in 2019 by another Senior Design team. Partnering with the pathology department at the University of Pennsylvania, they collected data, built interfaces to help pathologists categorize the data, and made great steps towards achieving their goal of creating a tool to output the density of the eosinophil cells in digital slides of human nasal tissue. 
    The  new 2021/2022 Digital Pathology team is working to continue the project the previous two teams laid out. By analyzing, reworking, and expanding upon the original code base, the current Digital Pathology team looks to improve the original project both in accuracy of cell detection and in identification time to where practicing pathologists may benefit from the use of the tool in actual medical cases.