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. 2009:5193098:518-521.
doi: 10.1109/ISBI.2009.5193098.

NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS

Luís Pedro Coelho  1 , Aabid Shariff, Robert F Murphy
Affiliations

NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS

Luís Pedro Coelho et al. Proc IEEE Int Symp Biomed Imaging. 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.

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Figures

Fig. 1
Fig. 1
Two example images from the U2OS collection. (a) shows nuclei that are well separated. Automatic segmentation is expected to do well. (b) has many clustered nuclei and is expected to challenge segmentation algorithms. Most images in the collection lie in between these two examples.
See this image and copyright information in PMC

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