Deep Learning Identifies Cardiomyocyte Nuclei With High Precision

Circ Res. 2020 Aug 14;127(5):696-698. doi: 10.1161/CIRCRESAHA.120.316672. Epub 2020 Jun 3.

Authors

Shah R Ali^#¹, Dan Nguyen^#², Brandon Wang^#², Steven Jiang², Hesham A Sadek^{1

3}

Affiliations

¹ From the Division of Cardiology; Department of Internal Medicine (S.R.A., H.A.S.), The University of Texas Southwestern Medical Center, Dallas.
² Department of Radiation Oncology, Medical Artificial Intelligence and Automation Laboratory (D.N., B.W., S.J.), The University of Texas Southwestern Medical Center, Dallas.
³ Center for Regenerative Science and Medicine (H.A.S.), The University of Texas Southwestern Medical Center, Dallas.

^# Contributed equally.

PMID: 32486999
DOI: 10.1161/CIRCRESAHA.120.316672

No abstract available

Keywords: epitope; machine learning; mice; myocytes, cardiac; nucleus.

Publication types

Letter
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Animals
Biomarkers / metabolism
Cell Nucleus / metabolism*
Deep Learning*
Fluorescent Dyes / chemistry
Image Processing, Computer-Assisted*
Immunohistochemistry
Indoles / chemistry
Integrases / genetics
Integrases / metabolism
Mice
Mice, Transgenic
Microscopy*
Myocytes, Cardiac / metabolism*
Myosin Heavy Chains / genetics
Reproducibility of Results
Troponin T / metabolism

Substances

Biomarkers
Fluorescent Dyes
Indoles
Myh6 protein, mouse
Troponin T
DAPI
Cre recombinase
Integrases
Myosin Heavy Chains