title: Automatic Cell Segmentation in Fluorescence Images of Confluent Cell Monolayers Using Multi-object Geometric Deformable Model.
abstract: With the rapid development of microscopy for cell imaging, there is a strong and growing demand for image analysis software to quantitatively study cell morphology. Automatic cell segmentation is an important step in image analysis. Despite substantial progress, there is still a need to improve the accuracy, efficiency, and adaptability to different cell morphologies. In this paper, we propose a fully automatic method for segmenting cells in fluorescence images of confluent cell monolayers. This method addresses several challenges through a combination of ideas. 1) It realizes a fully automatic segmentation process by first detecting the cell nuclei as initial seeds and then using a multi-object geometric deformable model (MGDM) for final segmentation. 2) To deal with different defects in the fluorescence images, the cell junctions are enhanced by applying an order-statistic filter and principal curvature based image operator. 3) The final segmentation using MGDM promotes robust and accurate segmentation results, and guarantees no overlaps and gaps between neighboring cells. The automatic segmentation results are compared with manually delineated cells, and the average Dice coefficient over all distinguishable cells is 0.88.
authors.affiliation: Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Yang
authors.affiliation: Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: John A
authors.initials: JA
authors.lastname: Bogovic
authors.affiliation: Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: Aaron
authors.initials: A
authors.lastname: Carass
authors.affiliation: Materials Science and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA ; Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: Mao
authors.initials: M
authors.lastname: Ye
authors.affiliation: Materials Science and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA ; Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: Peter C
authors.initials: PC
authors.lastname: Searson
authors.affiliation: Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA ; Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
authors.forename: Jerry L
authors.initials: JL
authors.lastname: Prince
keywords: Cell segmentation; cell junction network; cell nuclei; immunofluorescence microscopy; multi-object geometric deformable model (MGDM)