Automated computational detection, quantitation, and mapping of mitosis in whole-slide images for clinically actionable surgical pathology decision support

Automated computational detection, quantitation, and mapping of mitosis in whole-slide images for clinically actionable surgical pathology decision support

Background: Determining mitotic index by counting mitotic figures (MFs) microscopically from tumor areas with most abundant MF (hotspots [HS]) produces a prognostically useful tumor grading biomarker. However, interobserver concordance identifying MF and HS can be poorly reproducible. Immunolabeling...

Full description

Bibliographic Details
Main Authors: Munish Puri, Shelley B Hoover, Stephen M Hewitt, Bih-Rong Wei, Hibret Amare Adissu, Charles H C Halsey, Jessica Beck, Charles Bradley, Sarah D Cramer, Amy C Durham, D Glen Esplin, Chad Frank, L Tiffany Lyle, Lawrence D McGill, Melissa D Sánchez, Paula A Schaffer, Ryan P Traslavina, Elizabeth Buza, Howard H Yang, Maxwell P Lee, Jennifer E Dwyer, R Mark Simpson
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2019-01-01
Series:Journal of Pathology Informatics
Subjects:
Cancer grading
computer-assisted diagnosis/prognosis
feature engineering
image segmentation
method reproducibility
pathology imaging informatics
proliferation index
Online Access:http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2019;volume=10;issue=1;spage=4;epage=4;aulast=Puri

Internet

http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2019;volume=10;issue=1;spage=4;epage=4;aulast=Puri

Similar Items