Abstract:BACKGROUND
Tunneling nanotubes (TNTs) are cellular structures connecting cell membranes and mediating intercellular communication. TNTs are manually identified and counted by a trained investigator; however, this process is time-intensive. We therefore sought to develop an automated approach for quantitative analysis of TNTs.
METHODS
We used the convolutional neural network (U-Net) deep learning model to segment phase contras… Show more
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