By Topic

Region growing segmentation of textured cell images

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 $31
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

3 Author(s)
Wu, H.-S. ; Dept. of Pathology, School of Med., New York, NY, USA ; Barba, J. ; Gil, J.

The authors introduce a region growing algorithm working in conjunction with the K-means algorithm for the segmentation of textured cell images. The iterative algorithm initially segments the most easily classifiable regions which are grown in subsequent iterations. Only the most easily classifiable pixels in the remaining regions are segmented in each iteration. Experimental results of the procedure in segmenting breast cancer cells are demonstrated and compared to the K-means algorithm

Published in:

Electronics Letters  (Volume:32 ,  Issue: 12 )