期刊
CYTOMETRY PART A
卷 81A, 期 5, 页码 409-418出版社
WILEY
DOI: 10.1002/cyto.a.22034
关键词
image segmentation; computer-assisted image processing; tissue analysis; confocal microscopy; Drosophila; embryogenesis
资金
- Human Frontier Science Program [RGP0021/2007C]
- National Science Foundation [IOB-0545679]
- National Institutes of Health [1R01GM099107]
To study the process of morphogenesis, one often needs to collect and segment time-lapse images of living tissues to accurately track changing cellular morphology. This task typically involves segmenting and tracking tens to hundreds of individual cells over hundreds of image frames, a scale that would certainly benefit from automated routines; however, any automated routine would need to reliably handle a large number of sporadic, and yet typical problems (e.g., illumination inconsistency, photobleaching, rapid cell motions, and drift of focus or of cells moving through the imaging plane). Here, we present a segmentation and cell tracking approach based on the premise that users know their data bestinterpreting and using image features that are not accounted for in any a priori algorithm design. We have developed a program, SeedWater Segmenter, that combines a parameter-less and fast automated watershed algorithm with a suite of manual intervention tools that enables users with little to no specialized knowledge of image processing to efficiently segment images with near-perfect accuracy based on simple user interactions. (c) 2012 International Society for Advancement of Cytometry
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