Automatic Quantification of Neutrophil Accumulation within the Alveolar Space in Lung Histology Images using Artificial Intelligence

This project aims to create advanced artificial intelligence (AI) tools to help scientists and doctors better understand and treat severe lung conditions, like acute lung injury (ALI). ALI is a serious condition that can lead to breathing problems and is often difficult to study because the current methods for analyzing lung tissue are time-consuming and rely heavily on human judgment. We plan to develop AI models that can automatically analyze images of lung tissue to count neutrophils, a type of white blood cell that is important in understanding inflammation in the lungs. Using cutting-edge machine learning techniques, including Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), our goal is to create a reliable system that not only speeds up the analysis process but also makes it more accurate. These AI tools will be able to explain how they arrive at their conclusions, making it easier for doctors and researchers to trust the results. Ultimately, this project could lead to better ways to study and treat lung diseases, improving patient care and potentially reducing healthcare costs.

Faculty Supervisor:

Majid Komeili

Student:

Partner:

Ottawa Hospital Research Institute

Discipline:

Computer science

Sector:

Health and Related Sciences & Technology; Professional, scientific and technical services

University:

Carleton University

Program: