Grant: Research Tools and Instruments
The University of British Columbia
$150,000.00
High-throughput microscope for AI-powered image cytometry
FY 2024-25
Summary
Cytometry, or the analysis of cells, is fundamentally important to many areas of biological research. Image cytometry is one form of cytometry performed by capturing high-resolution images of cells using a microscope. This approach can acquire high-quality images of cell morphology, is tolerant of different cell sizes, and can assess many types of cell behaviours and functions. A fundamental need for image cytometry is the rapid acquisition large amount of high-quality microscopy data to capture the full heterogeneity of biological samples. This need is especially important for emerging studies that use artificial intelligence to perform deep analysis of cell image data.
This proposal requests funding for a high-throughput microscope system to fill critical needs in several multi-disciplinary research programs in image cytometry. The requested microscope can acquire microscopy images at ~20X speed of conventional microscopes. This equipment will support research programs spanning a wide range of disciplines, including AI-powered image cytometry, stain-free drug screening, image-based cell separation, analysis of cardiomyocyte contractility, development of organ-on-a-chip microfluidic systems, and elucidate the molecular mechanisms of cytokine secretion. The requested microscope system provides a versatile platform for HQP training at the graduate, undergraduate, and postdoctoral level. Trainees will be able to use this platform to develop valuable skills in large scale microscopy data acquisition and analysis.
Program
Research Tools and Instruments
Recipient
Location
British Columbia, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RTI-2025-00567
Name nom
Ma, Hongshen
Department département
Mechanical Engineering - Mechanical Engineering
Organization id
2
Institution établissement
The University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2025
Award amount
150000
Program id
RTI
Program name en
Research Tools and Instruments
Program name fr
Outils et instruments de recherche
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1612
Committee name en
Mechanical Engineering (RTI)
Committee name fr
Génie mecanique (OIR)
Area of application code
1102
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Biomedical engineering
Area of application fr
Génie biomédical
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
High-throughput microscope for AI-powered image cytometry
Keywords
artificial intelligence; machine learning; microscopy; cytometry; imaging; organ-on-a-chip; spheroids; biomaterials
Application summary
Cytometry, or the analysis of cells, is fundamentally important to many areas of biological research. Image cytometry is one form of cytometry performed by capturing high-resolution images of cells using a microscope. This approach can acquire high-quality images of cell morphology, is tolerant of different cell sizes, and can assess many types of cell behaviours and functions. A fundamental need for image cytometry is the rapid acquisition large amount of high-quality microscopy data to capture the full heterogeneity of biological samples. This need is especially important for emerging studies that use artificial intelligence to perform deep analysis of cell image data.
This proposal requests funding for a high-throughput microscope system to fill critical needs in several multi-disciplinary research programs in image cytometry. The requested microscope can acquire microscopy images at ~20X speed of conventional microscopes. This equipment will support research programs spanning a wide range of disciplines, including AI-powered image cytometry, stain-free drug screening, image-based cell separation, analysis of cardiomyocyte contractility, development of organ-on-a-chip microfluidic systems, and elucidate the molecular mechanisms of cytokine secretion. The requested microscope system provides a versatile platform for HQP training at the graduate, undergraduate, and postdoctoral level. Trainees will be able to use this platform to develop valuable skills in large scale microscopy data acquisition and analysis.