By Topic

Nuclear segmentation in microscope cell images: A hand-segmented dataset and comparison of algorithms

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

3 Author(s)
Coelho, L.P. ; Lane Center for Comput. Biol., Carnegie Mellon Univ., Pittsburgh, PA, USA ; Shariff, A. ; Murphy, R.F.

Image segmentation is an essential step in many image analysis pipelines and many algorithms have been proposed to solve this problem. However, they are often evaluated subjectively or based on a small number of examples. To fill this gap, we hand-segmented a set of 97 fluorescence microscopy images (a total of 4009 cells) and objectively evaluated some previously proposed segmentation algorithms. We focus on algorithms appropriate for high-throughput settings, where only minimal user intervention is feasible. The hand-labeled dataset (and all software used to compare methods) is publicly available to enable others to use it as a benchmark for newly proposed algorithms.

Published in:

Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on

Date of Conference:

June 28 2009-July 1 2009