Skip to content

Latest commit

 

History

History
21 lines (17 loc) · 1.26 KB

README.md

File metadata and controls

21 lines (17 loc) · 1.26 KB

DOI:10.1109/TIPTEKNO50054.2020.9299213

Explanation

  • End to end cell tracking code.
  • Collective cell analysis from microscopy image series is important for wound healing research. Computer-based automation of such analyses may help in rapid acquisition of reliable and reproducible results.
  • In this study phase-contrast optical microscopy image series of an in-vitro wound healing essay is manually delineated by two experts and its analysis is realized. Traditional image processing and deep learning based approaches for automated segmentation of wound area are developed and compared.
  • Please check the paper for more details.

Cite

If you find this work useful, please cite:

@INPROCEEDINGS{9299213,
author={Mayalıve, Berkay and Şaylığ, Orkun and Özuysal, Özden Y. and Okvur, Devrim P. and Töreyin, Behçet Ugur and Ünay, Devrim},
booktitle={2020 Medical Technologies Congress (TIPTEKNO)},
title={Automated Analysis of Wound Healing Microscopy Image Series - A Preliminary Study},
year={2020},
volume={},
number={},
pages={1-4},
doi={10.1109/TIPTEKNO50054.2020.9299213}}