Enhanced accuracy and reliability of ER and PR immunohistochemistry scoring using ANN from digital microscope images
Joint Authors
Ismail, Haydar Jalal
Abu Bakr, Salah
Yaba, Sardar Pirkhider
Source
ZANCO Journal of Pure and Applied Sciences
Issue
Vol. 27, Issue 5 (30 Sep. 2015), pp.69-80, 12 p.
Publisher
Salahaddin University-Erbil Department of Scientific Publications
Publication Date
2015-09-30
Country of Publication
Iraq
No. of Pages
12
Main Subjects
Topics
Abstract EN
ER (Estrogen receptor) and PR (Progesterone receptor) are breast oncogene receptors that are important for the growth of some organs.
Their statuses for breast cancer patients are vital to determine chemical therapy for the patients after surgical removal of cancer.
A computer program programmed by the author in Matlab language to study each type of receptors (10 slide images studied for each one).
The program used pixel color classification techniques by using Artificial Neural Network (ANN).
As a results: Some images resizing, re-dimensioning, and enhancing are done by photoshop program and that aimed to obtain better results of Proportion Observation percent (PO%).
The PO% estimated for ER and PR receptors by two methods; pathologist method (manual scoring), and by computer (computer scoring).
Results of the methods are close to each other for ER and PR receptors and statistical evaluation confirmed that the program can be used as an objective method to confirm the first method.
Computer program was better than the manual method for PO% computation because it is an objective method and shows results in very accurate manner.
American Psychological Association (APA)
Ismail, Haydar Jalal& Abu Bakr, Salah& Yaba, Sardar Pirkhider. 2015. Enhanced accuracy and reliability of ER and PR immunohistochemistry scoring using ANN from digital microscope images. ZANCO Journal of Pure and Applied Sciences،Vol. 27, no. 5, pp.69-80.
https://search.emarefa.net/detail/BIM-668632
Modern Language Association (MLA)
Ismail, Haydar Jalal…[et al.]. Enhanced accuracy and reliability of ER and PR immunohistochemistry scoring using ANN from digital microscope images. ZANCO Journal of Pure and Applied Sciences Vol. 27, no. 5 (2015), pp.69-80.
https://search.emarefa.net/detail/BIM-668632
American Medical Association (AMA)
Ismail, Haydar Jalal& Abu Bakr, Salah& Yaba, Sardar Pirkhider. Enhanced accuracy and reliability of ER and PR immunohistochemistry scoring using ANN from digital microscope images. ZANCO Journal of Pure and Applied Sciences. 2015. Vol. 27, no. 5, pp.69-80.
https://search.emarefa.net/detail/BIM-668632
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 79-80
Record ID
BIM-668632