Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies
Author:
Funder
ITEA3
Publisher
Springer Science and Business Media LLC
Subject
Cell Biology,Molecular Biology,General Medicine,Pathology and Forensic Medicine
Link
http://link.springer.com/content/pdf/10.1007/s00428-019-02577-x.pdf
Reference28 articles.
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3. Heidenreich A, Bastian PJ, Bellmunt J, Bolla M, Joniau S, van der Kwast T, Mason M, Matveev V, Wiegel T, Zattoni F, Mottet N (2014) EAU guidelines on prostate cancer. Part 1: screening, diagnosis, and local treatment with curative intent - update 2013. Eur Urol 65:124–137. https://doi.org/10.1016/j.eururo.2013.09.046
4. Epstein JI, Allsbrook WCJ, Amin MB, Egevad LL (2005) The 2005 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma. Am J Surg Pathol 29:1228–1242. https://doi.org/10.1097/01.pas.0000173646.99337.b1
5. Epstein JI, Zelefsky MJ, Sjoberg DD, Nelson JB, Egevad L, Magi-Galluzzi C, Vickers AJ, Parwani AV, Reuter VE, Fine SW, Eastham JA, Wiklund P, Han M, Reddy CA, Ciezki JP, Nyberg T, Klein EA (2016) A contemporary prostate Cancer grading system: a validated alternative to the Gleason score. Eur Urol 69:428–435. https://doi.org/10.1016/j.eururo.2015.06.046
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