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Phantoms Improve Robustness of Deep Learning Automated Segmentation in Cryotomography

Published online by Cambridge University Press:  22 July 2022

Jessica Heebner ,
Carson Purnell ,
Mike Marsh  and
Matthew Swulius
Jessica Heebner
Affiliation:
Pennsylvania State University College of Medicine. Department of Biochemistry and Molecular Biology Hershey, PA, USA
Carson Purnell
Affiliation:
Pennsylvania State University College of Medicine. Department of Biochemistry and Molecular Biology Hershey, PA, USA
Mike Marsh
Affiliation:
Object Research Systems. Denver, CO, USA
Matthew Swulius*
Affiliation:
Pennsylvania State University College of Medicine. Department of Biochemistry and Molecular Biology Hershey, PA, USA
*
*Corresponding Author: [email protected]

Abstract

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Type
Technical Advances in Cryo-EM
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 1226 - 1228
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Copyright
Copyright © Microscopy Society of America 2022

References

Chreifi, G., S et al. , Journal of Structural Biology, 205 (2019) 163–169. https://doi.org/10.1016/j.jsb.2018.12.008.CrossRefGoogle Scholar
Chreifi, G., Chen, S., & Jensen, G. J., Journal of Structural Biology, 213 (2021) 107716. https://doi.org/10.1016/j.jsb.2021.107716.CrossRefGoogle Scholar
Lee, S. M., J et al. , Journal of Thoracic Imaging, 34 (2019) 75–85. https://doi.org/10.1097/RTI.0000000000000387.CrossRefGoogle Scholar
Moen, E. et al. , Nat Methods, 16 (2019) 1233–1246. https://doi.org/10.1038/s41592-019-0403-1.CrossRefGoogle Scholar
Wang, K., Nature Methods, 18 (2022) 454–462. https://doi.org/10.1038/s41592-021-01151-1.Google Scholar
Ting, D. S. W. et al. , Progress in Retinal and Eye Research, 72 (2019). https://doi.org/10.1016/j.preteyeres.2019.04.003.CrossRefGoogle Scholar
Holbrook, M. D. et al. , Tomography, 7 (2021) 358–372. https://doi.org/10.3390/tomography7030032.CrossRefGoogle Scholar
Malimban, J. et al. , Scientific Reports, 12 (2022) 1822. https://doi.org/10.1038/s41598-022-05868-7.CrossRefGoogle Scholar
Chen, M. et al. , Nature Methods, 14 (2017) 983–985. https://doi.org/10.1038/nmeth.4405.CrossRefGoogle Scholar
Moebel, E., A et al. , Nature Methods, 18 (2021) 1386–1394. https://doi.org/10.1038/s41592-021-01275-4.CrossRefGoogle Scholar
Buchholz, T. O., Jordan, M., Pigino, G., & Jug, F., Proceedings - International Symposium on Biomedical Imaging, April (2019) 502–506. https://doi.org/10.1109/ISBI.2019.8759519.Google Scholar
Du, X., H et al. , Bioinformatics, 37 (2021) 2340–2346. https://doi.org/10.1093/bioinformatics/btab123.CrossRefGoogle Scholar
Liu, Y.-T. et al. , bioRxiv, (2021). https://doi.org/10.1101/2021.07.17.452128.Google Scholar
TOM Toolbox | Max Planck Institute of Biochemistry. https://www.biochem.mpg.de/6348566/tom_eGoogle Scholar
Dragonfly 2021.3 (Computer Software). (2021) http://www.theobjects.com/dragonfly.Google Scholar
Provencher, B., Ruslana, M., Yen, E., Piche, N., & Marsh, M., Microscopy and Microanalysis, 25 (2019) 1388–1389.CrossRefGoogle Scholar
Heebner, J. and Purnell, C. contributed equally to this research.Google Scholar