title: A rapid and efficient 2D/3D nuclear segmentation method for analysis of early mouse embryo and stem cell image data.
abstract: Segmentation is a fundamental problem that dominates the success of microscopic image analysis. In almost 25 years of cell detection software development, there is still no single piece of commercial software that works well in practice when applied to early mouse embryo or stem cell image data. To address this need, we developed MINS (modular interactive nuclear segmentation) as a MATLAB/C++-based segmentation tool tailored for counting cells and fluorescent intensity measurements of 2D and 3D image data. Our aim was to develop a tool that is accurate and efficient yet straightforward and user friendly. The MINS pipeline comprises three major cascaded modules: detection, segmentation, and cell position classification. An extensive evaluation of MINS on both 2D and 3D images, and comparison to related tools, reveals improvements in segmentation accuracy and usability. Thus, its accuracy and ease of use will allow MINS to be implemented for routine single-cell-level image analyses.
authors.affiliation: Developmental Biology Program, Sloan-Kettering Institute, New York, NY 10065, USA.
authors.forename: Xinghua
authors.initials: X
authors.lastname: Lou
authors.affiliation: Developmental Biology Program, Sloan-Kettering Institute, New York, NY 10065, USA ; Department of Biochemistry, Cell and Molecular Biology Program, Weill Graduate School of Medical Sciences of Cornell University, New York, NY 10065, USA.
authors.forename: Minjung
authors.initials: M
authors.lastname: Kang
authors.affiliation: Developmental Biology Program, Sloan-Kettering Institute, New York, NY 10065, USA.
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Xenopoulos
authors.affiliation: Developmental Biology Program, Sloan-Kettering Institute, New York, NY 10065, USA.
authors.forename: Silvia
authors.initials: S
authors.lastname: Muñoz-Descalzo
authors.affiliation: Developmental Biology Program, Sloan-Kettering Institute, New York, NY 10065, USA.
authors.forename: Anna-Katerina
authors.initials: AK
authors.lastname: Hadjantonakis
mesh_terms: D000465:Algorithms; D000818:Animals; D004622:Embryo, Mammalian / Q000166:cytology* / Q000378:metabolism; D053595:Embryonic Stem Cells / Q000166:cytology* / Q000378:metabolism; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D051379:Mice; D008853:Microscopy / Q000379:methods; D012984:Software