title: NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS.
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.
authors.affiliation: Lane Center for Computational Biology, Carnegie Mellon University.
authors.forename: Luís Pedro
authors.initials: LP
authors.lastname: Coelho
authors.forename: Aabid
authors.initials: A
authors.lastname: Shariff
authors.forename: Robert F
authors.initials: RF
authors.lastname: Murphy