Automatic and Manual Proliferation Rate Estimation from Digital Pathology Images ()
ABSTRACT
Digital pathology is a major revolution in
pathology and is changing the clinical routine for pathologists. We work on
providing a computer aided diagnosis system that automatically and robustly
provides the pathologist with a second opinion for many diagnosis tasks.
However, inter-observer variability prevents thorough validation of any
proposed technique for any specific problems. In this work, we study the
variability and reliability of proliferation rate estimation from digital
pathology images for breast cancer proliferation rate estimation. We also study
the robustness of our recently proposed method CAD system for PRE estimation.
Three statistical significance tests showed that our automated CAD system was
as reliable as the expert pathologist in both brown and blue nuclei estimation
on a dataset of 100 images.
Share and Cite:
Rajab, L. , Al-Lahham, H. , Alomari, R. , Obaidat, F. and Chaudhary, V. (2015) Automatic and Manual Proliferation Rate Estimation from Digital Pathology Images.
Journal of Software Engineering and Applications,
8, 269-275. doi:
10.4236/jsea.2015.86027.
Cited by
No relevant information.