Statistical analysis of survival models using feature quantification on prostate cancer histopathological images

Statistical analysis of survival models using feature quantification on prostate cancer histopathological images

Background: Grading of prostatic adenocarcinoma is based on the Gleason scoring system and the more recently established prognostic grade groups. Typically, prostate cancer grading is performed by pathologists based on the morphology of the tumor on hematoxylin and eosin (H and E) slides. In this st...

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Bibliographic Details
Main Authors: Jian Ren, Eric A Singer, Evita Sadimin, David J Foran, Xin Qi
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2019-01-01
Series:Journal of Pathology Informatics
Subjects:
histopathological image
image features
neural networks
prostate cancer
survival models
Online Access:http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2019;volume=10;issue=1;spage=30;epage=30;aulast=Ren

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http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2019;volume=10;issue=1;spage=30;epage=30;aulast=Ren

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