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Hamza Ergüder on Muck Rack

Hamza Ergüder

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Articles

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

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By Katherine J. Ladner, Sophie Korenfeld, Yasin Ceran, Hamza Ergüder
| Texas Medical Center
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 a convolutional neural network (U-Net) deep learning model to segment phase contrast microscopy images of both cancer and non-cancer cells.
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