Computational tools for automated histological image analysis and quantification in cardiac tissue

Daniel Gratz; Alexander J Winkle; Alyssa Dalic; Sathya D Unudurthi; Thomas J Hund

doi:10.1016/j.mex.2019.11.028

Computational tools for automated histological image analysis and quantification in cardiac tissue

MethodsX. 2019 Dec 7:7:22-34. doi: 10.1016/j.mex.2019.11.028. eCollection 2020.

Authors

Daniel Gratz^{1

2}, Alexander J Winkle^{1

2}, Alyssa Dalic^{1

2}, Sathya D Unudurthi^{1

2}, Thomas J Hund^{1

2

3}

Affiliations

¹ The Frick Center for Heart Failure and Arrhythmia, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
² Department of Biomedical Engineering, College of Engineering, The Ohio State University, Columbus, OH, USA.
³ Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA.

Abstract

Image processing and quantification is a routine and important task across disciplines in biomedical research. Understanding the effects of disease on the tissue and organ level often requires the use of images, however the process of interpreting those images into data which can be tested for significance is often time intensive, tedious and prone to inaccuracy or bias. When working within resource constraints, these different issues often present a trade-off between time invested in analysis and accuracy. To address these issues, we present two novel open source and publically available tools for automated analysis of histological cardiac tissue samples: •Automated Fibrosis Analysis Tool (AFAT) for quantifying fibrosis; and•Macrophage Analysis Tool (MAT) for quantifying infiltrating macrophages.

Keywords: Automated histological image analysis; Fibrosis; Heart failure; Histology; Image processing; Macrophage.

Abstract

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