title: FogBank: a single cell segmentation across multiple cell lines and image modalities.
abstract: BACKGROUND
  Many cell lines currently used in medical research, such as cancer cells or stem cells, grow in confluent sheets or colonies. The biology of individual cells provide valuable information, thus the separation of touching cells in these microscopy images is critical for counting, identification and measurement of individual cells. Over-segmentation of single cells continues to be a major problem for methods based on morphological watershed due to the high level of noise in microscopy cell images. There is a need for a new segmentation method that is robust over a wide variety of biological images and can accurately separate individual cells even in challenging datasets such as confluent sheets or colonies.
  
  
  RESULTS
  We present a new automated segmentation method called FogBank that accurately separates cells when confluent and touching each other. This technique is successfully applied to phase contrast, bright field, fluorescence microscopy and binary images. The method is based on morphological watershed principles with two new features to improve accuracy and minimize over-segmentation. First, FogBank uses histogram binning to quantize pixel intensities which minimizes the image noise that causes over-segmentation. Second, FogBank uses a geodesic distance mask derived from raw images to detect the shapes of individual cells, in contrast to the more linear cell edges that other watershed-like algorithms produce. We evaluated the segmentation accuracy against manually segmented datasets using two metrics. FogBank achieved segmentation accuracy on the order of 0.75 (1 being a perfect match). We compared our method with other available segmentation techniques in term of achieved performance over the reference data sets. FogBank outperformed all related algorithms. The accuracy has also been visually verified on data sets with 14 cell lines across 3 imaging modalities leading to 876 segmentation evaluation images.
  
  
  CONCLUSIONS
  FogBank produces single cell segmentation from confluent cell sheets with high accuracy. It can be applied to microscopy images of multiple cell lines and a variety of imaging modalities. The code for the segmentation method is available as open-source and includes a Graphical User Interface for user friendly execution.
authors.affiliation: Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. joe.chalfoun@nist.gov.
authors.forename: Joe
authors.initials: J
authors.lastname: Chalfoun
authors.affiliation: Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. michael.majurski@nist.gov.
authors.forename: Michael
authors.initials: M
authors.lastname: Majurski
authors.affiliation: Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. alden.dima@nist.gov.
authors.forename: Alden
authors.initials: A
authors.lastname: Dima
authors.affiliation: Laboratory of Cellular and Molecular Biology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. chrisstu@mail.nih.gov.
authors.forename: Christina
authors.initials: C
authors.lastname: Stuelten
authors.affiliation: Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. adele.peskin@nist.gov.
authors.forename: Adele
authors.initials: A
authors.lastname: Peskin
authors.affiliation: Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA. mary.brady@nist.gov.
authors.forename: Mary
authors.initials: M
authors.lastname: Brady
mesh_terms: D000465:Algorithms; D000818:Animals; D001940:Breast / Q000166:cytology; D002477:Cells / Q000166:cytology*; D019295:Computational Biology / Q000379:methods*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D051379:Mice; D008856:Microscopy, Fluorescence / Q000379:methods*; D008858:Microscopy, Phase-Contrast / Q000379:methods*; D041681:NIH 3T3 Cells; D012441:Saccharomyces cerevisiae / Q000166:cytology