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Analyzing Cell-Scaffold Interaction through Unsupervised 3D Nuclei Segmentation
Acknowledgments Nuclei Based on Concave Curve Expansion. J Microsc,

This work was financially supported by Key Program 251:57–67.
Special Fund in Xi’an Jiaotong-Liverpool University https://doi.org/10.1111/jmi.12043
under Grant KSF-E-37. 10. Xing F, Yang L, 2016. Robust Nucleus/Cell Detection and
Segmentation in Digital Pathology and Microscopy Images:
Conflict of interest A Comprehensive Review. IEEE Rev Biomed Eng, 9:234–63.
The authors declare that there is no conflict of interest. https://doi.org/10.1109/RBME.2016.2515127
11. Yang Z, Bogovic JA, Carass A, et al. 2013. Automatic Cell
Author contributions Segmentation in Fluorescence Images of Confluent Cell
K.Y., L.J., and H.L. designed the overall experimental Monolayers Using Multi-object Geometric Deformable
plan and performed experiments. K.Y. interpreted data Model. Proc SPIE Int Soc Opt Eng, 8669:2006603.
and wrote the manuscript with support from D.H. and https://doi.org/10.1117/12.2006603
K.H. J.S. supervised the project and conceived the original 12. McQuin C, Goodman A, Chernyshev V, et al. 2018.
idea. All authors read and approved the manuscript.
CellProfiler 3.0: Next-generation Image Processing for
References Biology. PLoS Biol, 16:e2005970.
https://doi.org/10.1371/journal.pbio.2005970
1. Ravi M, Paramesh V, Kaviya SR., et al. 2015. 3D Cell Culture 13. Rizk A, Paul G, Incardona P, et al., 2014. Segmentation and
Systems: Advantages and Applications. J Cell Physiol, Quantification of Subcellular Structures in Fluorescence
230:16–26. Microscopy Images Using Squassh. Nat Protoc, 9:6–596.
https://doi.org/10.1002/jcp.24683 https://doi.org/10.1038/nprot.2014.037
2. Pampaloni F, Reynaud EG, Stelzer EH, 2007. The Third 14. Kumar N, Verma R, Sharma S, et al., 2017. A Dataset
Dimension Bridges the Gap between Cell Culture and Live and a Technique for Generalized Nuclear Segmentation
Tissue. Nat Rev Mol Cell Biol, 8:839–45. for Computational Pathology. IEEE Trans Med Imaging,
https://doi.org/10.1038/nrm2236 36:1550–60.
3. Paddock SW, 1999. Confocal Laser Scanning Microscopy. 15. Xing F, Xie Y, Yang L, 2015. An Automatic Learning-based
Biotechniques, 27:992–1004. Framework for Robust Nucleus Segmentation. IEEE Trans
https://doi.org/10.2144/99275ov01 Med Imaging, 35:550–66.
4. Al-Kofahi Y, Zaltsman A, Graves R, et al. 2018. A Deep 16. Dunn KW, Fu C, Ho DJ, et al. 2019. DeepSynth: Three-
Learning-based Algorithm for 2-D Cell Segmentation in dimensional Nuclear Segmentation of Biological Images
Microscopy Images. BMC Bioinformatics, 19:1–11. Using Neural Networks Trained with Synthetic Data. Sci Rep,
5. Vahadane A and Sethi A, 2013. Towards Generalized 9:1–15.
Nuclear Segmentation in Histological Images. In: 17. Liu D, Zhang D, Song Y, et al. 2020. Unsupervised Instance
13 IEEE International Conference on Bioinformatics and Segmentation in Microscopy Images Via Panoptic Domain
th
Bioengineering. p1-4. Adaptation and Task Re-weighting. In: Proceedings of the
6. Xue JH, Titterington DM, 2011. t-Tests, f-Tests and Otsu’s IEEE/CVF Conference on Computer Vision and Pattern
methods for image thresholding. IEEE Trans Image Proc, Recognition. p4243-4252.
20:2392–96. 18. Hou L, Agarwal A, Samaras D, et al., 2019. Robust
https://doi.org/10.1109/TIP.2011.2114358 Histopathology Image Analysis: To Label or to Synthesize?
7. Jie S, Hong GS, Rahman M, et al., 2002. Feature Extraction In: Proceedings of the IEEE/CVF Conference on Computer
and Selection in tool Condition Monitoring System. In: Vision and Pattern Recognition. p8533-8542.
Australian Joint Conference on Artificial Intelligence. Berlin, 19. Yang J, Dvornek NC, Zhang F, et al., 2019. Unsupervised
Heidelberg: Springer. p487-497. Domain Adaptation Via Disentangled Representations:
8. Veta M, Van Diest PJ, Kornegoor R, et al. 2013. Automatic Application to Cross-modality Liver Segmentation. In:
Nuclei Segmentation in H&E Stained Breast Cancer International Conference on Medical Image Computing and
Histopathology Images. PLoS One, 8:e70221. Computer-Assisted Intervention. p255-263.
https://doi.org/10.1371/journal.pone.0070221 20. Sun J, Jing L, Liu H, et al., 2020. Generating Nanotopography
9. Zhang C, Sun C, Pham TD, 2013. Segmentation of Clustered on PCL Microfiber Surface for Better Cell-Scaffold
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