title: Automatic single cell segmentation on highly multiplexed tissue images.
abstract: The combination of mass cytometry and immunohistochemistry (IHC) enables new histopathological imaging methods in which dozens of proteins and protein modifications can be visualized simultaneously in a single tissue section. The power of multiplexing combined with spatial information and quantification was recently illustrated on breast cancer tissue and was described as next-generation IHC. Robust, accurate, and high-throughput cell segmentation is crucial for the analysis of this new generation of IHC data. To this end, we propose a watershed-based cell segmentation, which uses a nuclear marker and multiple membrane markers, the latter automatically selected based on their correlation. In comparison with the state-of-the-art segmentation pipelines, which are only using a single marker for object detection, we could show that the use of multiple markers can significantly increase the segmentation power, and thus, multiplexed information should be used and not ignored during the segmentation. Furthermore, we provide a novel, user-friendly open-source toolbox for the automatic segmentation of multiplexed histopathological images.
authors.affiliation: Department of Computer Science, ETH Zurich, Zurich, 8092, Switzerland.|Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Zurich, Switzerland.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Schüffler
authors.affiliation: Life Science Zurich Graduate School, ETH Zurich and University of Zurich, Zurich, Switzerland.|Institute of Molecular Life Sciences, University of Zurich, Zurich, 8057, Switzerland.
authors.forename: Denis
authors.initials: D
authors.lastname: Schapiro
authors.affiliation: Institute of Molecular Life Sciences, University of Zurich, Zurich, 8057, Switzerland.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Giesen
authors.affiliation: Department of Chemistry, ETH Zurich, Zurich, 8093, Switzerland.
authors.forename: Hao A O
authors.initials: HA
authors.lastname: Wang
authors.affiliation: Institute of Molecular Life Sciences, University of Zurich, Zurich, 8057, Switzerland.
authors.forename: Bernd
authors.initials: B
authors.lastname: Bodenmiller
authors.affiliation: Department of Computer Science, ETH Zurich, Zurich, 8092, Switzerland.
authors.forename: Joachim M
authors.initials: JM
authors.lastname: Buhmann
mesh_terms: D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology; D003952:Diagnostic Imaging / Q000379:methods*; D005260:Female; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D007150:Immunohistochemistry; D059010:Single-Cell Analysis
keywords: cell segmentation; mass cytometry; multiplexed imaging; single cell proteomics