Bringing Open Data to Whole Slide Imaging-Reference-Cited by-同舟云学术

Bringing Open Data to Whole Slide Imaging

Published:2019 Issue: Volume: Page:3-10
ISSN:0302-9743
Container-title:Digital Pathology
language:
Short-container-title:

Author:

Besson Sébastien^ORCID,Leigh Roger^ORCID,Linkert Melissa,Allan Chris,Burel Jean-Marie^ORCID,Carroll Mark^ORCID,Gault David,Gozim Riad,Li Simon^ORCID,Lindner Dominik^ORCID,Moore Josh^ORCID,Moore Will^ORCID,Walczysko Petr,Wong Frances^ORCID,Swedlow Jason R.^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-23937-4_1

Reference23 articles.

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2. Lin, J.-R., et al.: Highly multiplexed immunofluorescence imaging of human tissues and tumors using t-CyCIF and conventional optical microscopes. Elife 7, 31657 (2018)

3. Goltsev, Y., et al.: Deep profiling of mouse splenic architecture with CODEX multiplexed imaging. Cell 174, 968–981.e15 (2018)

4. Leo, P., et al.: Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study. Sci. Rep. 8, 14918 (2018)

5. Beig, N., et al.: Perinodular and intranodular radiomic features on lung CT images distinguish adenocarcinomas from granulomas. Radiology 290, 783–792 (2018). https://doi.org/10.1148/radiol.2018180910

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