Radio-pathomic mapping model generated using annotations from five pathologists reliably distinguishes high-grade prostate cancer

Purpose: Our study predictively maps epithelium density in magnetic resonance imaging (MRI) space while varying the ground truth labels provided by five pathologists to quantify the downstream effects of interobserver variability. Approach: Clinical imaging and postsurgical tissue from 48 recruited...

Szczegółowa specyfikacja

Zapisane w:
Opis bibliograficzny
Wydane w:J Med Imaging (Bellingham)
Główni autorzy: McGarry, Sean D., Bukowy, John D., Iczkowski, Kenneth A., Lowman, Allison K., Brehler, Michael, Bobholz, Samuel, Nencka, Andrew, Barrington, Alex, Jacobsohn, Kenneth, Unteriner, Jackson, Duvnjak, Petar, Griffin, Michael, Hohenwalter, Mark, Keuter, Tucker, Huang, Wei, Antic, Tatjana, Paner, Gladell, Palangmonthip, Watchareepohn, Banerjee, Anjishnu, LaViolette, Peter S.
Format: Artigo
Język:Inglês
Wydane: Society of Photo-Optical Instrumentation Engineers 2020
Hasła przedmiotowe:
Computer-Aided Diagnosis
Dostęp online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7479263/
https://ncbi.nlm.nih.gov/pubmed/32923510
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/1.JMI.7.5.054501
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