Virtual cell imaging: A review on simulation methods employed in image cytometry
| Authors | |
|---|---|
| Year of publication | 2016 |
| Type | Article in Periodical |
| Magazine / Source | Cytometry Part A |
| MU Faculty or unit | |
| Citation | |
| web | http://dx.doi.org/10.1002/cyto.a.23031 |
| Doi | http://dx.doi.org/10.1002/cyto.a.23031 |
| Field | Use of computers, robotics and its application |
| Keywords | cell imaging; virtual imaging; simulation; digital cell; cell model; digital phantom; ground truth; validation; image cytometry |
| Description | The simulations of cells and microscope images thereof have been used to facilitate the development, selection, and validation of image analysis algorithms employed in cytometry as well as for modeling and understanding cell structure and dynamics beyond what is visible in the eyepiece. The simulation approaches vary from simple parametric models of specific cell components—especially shapes of cells and cell nuclei—to learning-based synthesis and multi-stage simulation models for complex scenes that simultaneously visualize multiple object types and incorporate various properties of the imaged objects and laws of image formation. This review covers advances in artificial digital cell generation at scales ranging from particles up to tissue synthesis and microscope image simulation methods, provides examples of the use of simulated images for various purposes ranging from subcellular object detection to cell tracking, and discusses how such simulators have been validated. Finally, the future possibilities and limitations of simulation-based validation are considered. |
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