By Topic

Automatic cell recognition in immunohistochemical gastritis stains using sequential thresholding and SVM network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Markiewicz, T. ; Dept. of Pathology Mil., Inst. of the Health Services, Warsaw ; Jochymski, C. ; Koktysz, R. ; Kozlowski, W.

The paper presents program for automatic cell recognition and counting in selected immunohistochemical stains in the gastritis diseases. It is applied to cytoplasm reactivity markers, such as chromogranin A, serotonin and somatostatin antibodies. The program uses the sequential thresholding algorithm in combination with artificial neural network of support vector machine (SVM) type, to recognize the nuclei of the separated cells. The constructed algorithm imitates the human view of the image. The support vector machine is used for recognition of the immunoreactivity of the separated cell. The results corresponding to the exemplary images, confirm good accuracy, comparable to the human expert.

Published in:

Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on

Date of Conference:

14-17 May 2008