A cell level automated approach for quantifying antibody staining in immunohistochemistry images. A structural approach for quantifying antibody staining in colonic cancer spheroid images by integrating image processing and machine learning towards the implementation of computer aided scoring of cancer markers.

A cell level automated approach for quantifying antibody staining in immunohistochemistry images. A structural approach for quantifying antibody staining in colonic cancer spheroid images by integrating image processing and machine learning towards the implementation of computer aided scoring of cancer markers.

Immunohistological (IHC) stained images occupy a fundamental role in the pathologist¿s diagnosis and monitoring of cancer development. The manual process of monitoring such images is a subjective, time consuming process that typically relies on the visual ability and experience level of the patholog...

Full description

Bibliographic Details
Main Author: Khorshed, Reema A.A.
Other Authors: Jiang, Jianmin
Language:en
Published: University of Bradford 2013
Subjects:
Image processing
Cancer
Immunohistological
Nuclei segmentation
Nuclei classification
Feature extraction
Automation
Antibody quantification
Antibody staining
Colonic cancer spheroid images
Cancer markers
Computer aided scoring
Machine learning
Online Access:http://hdl.handle.net/10454/5763

Internet

http://hdl.handle.net/10454/5763

Similar Items