TNTdetect.AI: A Deep Learning Model for Automated Detection and Counting of Tunneling Nanotubes in Microscopy Images

TNTdetect.AI: A Deep Learning Model for Automated Detection and Counting of Tunneling Nanotubes in Microscopy Images

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 qu...

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Bibliographic Details
Main Authors: Yasin Ceran, Hamza Ergüder, Katherine Ladner, Sophie Korenfeld, Karina Deniz, Sanyukta Padmanabhan, Phillip Wong, Murat Baday, Thomas Pengo, Emil Lou, Chirag B. Patel
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Cancers
Subjects:
artificial intelligence
automated cell counting
biomarker
cancer
cells
deep learning
Online Access:https://www.mdpi.com/2072-6694/14/19/4958

Internet

https://www.mdpi.com/2072-6694/14/19/4958

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