Optimizing Fiji (ImageJ) for Quantifying Cardiomyocyte Differentiation from Induced Pluripotent Stem Cells
Session Number
2
Advisor(s)
Dr. Angel Alvarez, Northwestern Feinberg School of Medicine
Location
A119
Discipline
Biology
Start Date
15-4-2026 11:10 AM
End Date
15-4-2026 11:55 AM
Abstract
This study builds on prior work optimizing Fiji (ImageJ), a widely used image-processing tool in cell and molecular biology, and develops a standard protocol to identify and quantify cardiomyocyte subtypes. The primary objective is to analyze different microscopy images of differentiating iPSC cultures using Fiji. This study will address the current challenges of accurately measuring cardiomyocyte differentiation efficiency, manual cell counting (as it is slow and subjective), and distinguishing cardiomyocytes from undifferentiated iPSCs. A variety of Fiji tools will be used. This includes thresholding, segmentation, watershed processing, and region of interest (ROI) detection. The different cell morphology and behavior across the different stages will be compared. Accordingly, the Fiji parameters will be adjusted, and the limitations of differentiated cell counting will be discussed. The result of this study will help determine morphological features that distinguish cardiomyocytes from iPSCs and help determine which image-analysis techniques will help produce the most precise and consistent counts. This work will help establish a reliable Fiji-based workflow for cardiomyocyte quantification, reduce human bias in cell counting, and improve the reproducibility in stem cell research, cardiovascular disease modeling, and drug/cardiotoxicity testing. In the future, this research can be applied into analysis of multicellular organisms.
Optimizing Fiji (ImageJ) for Quantifying Cardiomyocyte Differentiation from Induced Pluripotent Stem Cells
A119
This study builds on prior work optimizing Fiji (ImageJ), a widely used image-processing tool in cell and molecular biology, and develops a standard protocol to identify and quantify cardiomyocyte subtypes. The primary objective is to analyze different microscopy images of differentiating iPSC cultures using Fiji. This study will address the current challenges of accurately measuring cardiomyocyte differentiation efficiency, manual cell counting (as it is slow and subjective), and distinguishing cardiomyocytes from undifferentiated iPSCs. A variety of Fiji tools will be used. This includes thresholding, segmentation, watershed processing, and region of interest (ROI) detection. The different cell morphology and behavior across the different stages will be compared. Accordingly, the Fiji parameters will be adjusted, and the limitations of differentiated cell counting will be discussed. The result of this study will help determine morphological features that distinguish cardiomyocytes from iPSCs and help determine which image-analysis techniques will help produce the most precise and consistent counts. This work will help establish a reliable Fiji-based workflow for cardiomyocyte quantification, reduce human bias in cell counting, and improve the reproducibility in stem cell research, cardiovascular disease modeling, and drug/cardiotoxicity testing. In the future, this research can be applied into analysis of multicellular organisms.