An Extensive Study: Creation of A New Inverted Microscope Image Data Set and Improving Auto-Encoder Models for Higher Accuracy Segmentation of HaCaT Cell Culture Line-Reference-Cited by-同舟云学术

An Extensive Study: Creation of A New Inverted Microscope Image Data Set and Improving Auto-Encoder Models for Higher Accuracy Segmentation of HaCaT Cell Culture Line

Published:2023-06-08 Issue: Volume: Page:
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Container-title:2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)
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Author:

Sevim Zeynep¹,Dogan Hulya²,Demir Zeynep³,Sezen Feride Sena³,Dogan Ramazan Ozgur⁴

Affiliation:

1. Gumushane University,Department of Artificial Intelligence and Intelligent Systems,Gumushane,Turkiye

2. Karadeniz Technical University,Faculty of Engineering,Department of Software Engineering,Trabzon,Turkiye

3. Karadeniz Technical University,Drug and Pharmaceutical Technology Application & Research Center,Trabzon,Turkiye

4. Gumushane University,Faculty of Engineering and Natural Sciences,Department of Software Engineering,Trabzon,Turkiye

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10156655/10155769/10156778.pdf?arnumber=10156778

Reference27 articles.

1. A survey on applications of deep learning in microscopy image analysis

2. Cell Nuclei and Cytoplasm Joint Segmentation Using the Sliding Band Filter

3. Deep learning for cell image segmentation and ranking

4. Deep-learning-based image segmentation integrated with optical microscopy for automatically searching for two-dimensional materials

5. A high-throughput imaging and nuclear segmentation analysis protocol for cleared 3D culture models

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