Fractal dimension-based viability analysis of cancer cell lines in lens-free holographic microscopy via machine learning-Reference-Cited by-同舟云学术

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Fractal dimension-based viability analysis of cancer cell lines in lens-free holographic microscopy via machine learning

Published:2021-11-26 Issue: Volume: Page:
ISSN:1951-6355
Container-title:The European Physical Journal Special Topics
language:en
Short-container-title:Eur. Phys. J. Spec. Top.

Author:

Pala Muhammed Ali^ORCID,Çimen Murat Erhan,Akgül Akif,Yıldız Mustafa Zahid,Boz Ali Fuat

Funder

Sakarya University of Applied Sciences

Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy,General Materials Science

Link

https://link.springer.com/content/pdf/10.1140/epjs/s11734-021-00342-3.pdf

Reference46 articles.

1. M. Wei et al., An evaluation approach of cell viability based on cell detachment assay in a single-channel integrated microfluidic chip. ACS Sens. 4(10), 2654–2661 (2019). https://doi.org/10.1021/acssensors.9b01061

2. K. Yang, J. Wu, S. Santos, Y. Liu, L. Zhu, F. Lin, Recent development of portable imaging platforms for cell-based assays. Biosens. Bioelectron. 124–125(October 2018), 150–160 (2019). https://doi.org/10.1016/j.bios.2018.10.024

3. J. Sun, A. Tárnok, X. Su, Deep learning-based single-cell optical image studies. Cytom. Part A 97(3), 226–240 (2020). https://doi.org/10.1002/cyto.a.23973

4. Y. Wu, A. Ozcan, Lensless digital holographic microscopy and its applications in biomedicine and environmental monitoring. Methods 136, 4–16 (2018). https://doi.org/10.1016/j.ymeth.2017.08.013

5. M. Sher, R. Zhuang, U. Demirci, W. Asghar, Paper-based analytical devices for clinical diagnosis: recent advances in the fabrication techniques and sensing mechanisms. Expert Rev. Mol. Diagn. 17(4), 351–366 (2017). https://doi.org/10.1080/14737159.2017.1285228

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