Deep learning-based quality control of cultured human-induced pluripotent stem cell-derived cardiomyocytes
Using bright-field images of cultured human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), we trained a convolutional neural network (CNN), a machine learning technique, to decide whether the qualities of cell cultures are suitable for experiments. VGG16, an open-source CNN framew...
Saved in:
Main Authors: | Ken Orita (Author), Kohei Sawada (Author), Ryuta Koyama (Author), Yuji Ikegaya (Author) |
---|---|
Format: | Book |
Published: |
Elsevier,
2019-08-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Mitochondrial Maturation in Human Pluripotent Stem Cell Derived Cardiomyocytes
by: Dao-Fu Dai, et al.
Published: (2017) -
Electrophysiological Characterization of Cardiomyocytes Derived From Human Induced Pluripotent Stem Cells
by: Masaki Honda, et al.
Published: (2011) -
Extracellular Recordings of Patterned Human Pluripotent Stem Cell-Derived Cardiomyocytes on Aligned Fibers
by: Junjun Li, et al.
Published: (2016) -
Proarrhythmia risk prediction using human induced pluripotent stem cell-derived cardiomyocytes
by: Daiju Yamazaki, et al.
Published: (2018) -
Ion Channel Expression and Characterization in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes
by: Zhihan Zhao, et al.
Published: (2018)