Title :
Nuclear segmentation in microscope cell images: A hand-segmented dataset and comparison of algorithms
Author :
Coelho, Luís Pedro ; Shariff, Aabid ; Murphy, Robert F.
Author_Institution :
Lane Center for Comput. Biol., Carnegie Mellon Univ., Pittsburgh, PA, USA
fDate :
June 28 2009-July 1 2009
Abstract :
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.
Keywords :
biomedical optical imaging; cellular biophysics; image segmentation; medical image processing; optical microscopy; cells; fluorescence microscopy; hand-labeled dataset; high-throughput settings; image analysis pipelines; image segmentation; microscope; Biomedical engineering; Biomedical informatics; Cells (biology); Computational biology; Fluorescence; Image segmentation; Machine learning; Machine learning algorithms; Microscopy; Pipelines; Biomedical image processing; Image segmentation;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2009.5193098