Paper
30 September 1994 Computational optical-sectioning microscopy for 3D quantization of cell motion: results and challenges
James G. McNally
Author Affiliations +
Abstract
How cells move and navigate within a 3D tissue mass is of central importance in such diverse problems as embryonic development, wound healing and metastasis. This locomotion can now be visualized and quantified by using computation optical-sectioning microscopy. In this approach, a series of 2D images at different depths in a specimen are stacked to construct a 3D image, and then with a knowledge of the microscope's point-spread function, the actual distribution of fluorescent intensity in the specimen is estimated via computation. When coupled with wide-field optics and a cooled CCD camera, this approach permits non-destructive 3D imaging of living specimens over long time periods. With these techniques, we have observed a complex diversity of motile behaviors in a model embryonic system, the cellular slime mold Dictyostelium. To understand the mechanisms which control these various behaviors, we are examining motion in various Dictyostelium mutants with known defects in proteins thought to be essential for signal reception, cell-cell adhesion or locomotion. This application of computational techniques to analyze 3D cell locomotion raises several technical challenges. Image restoration techniques must be fast enough to process numerous 1 Gbyte time-lapse data sets (16 Mbytes per 3D image X 60 time points). Because some cells are weakly labeled and background intensity is often high due to unincorporated dye, the SNR in some of these images is poor. Currently, the images are processed by a regularized linear least- squares restoration method, and occasionally by a maximum-likelihood method. Also required for these studies are accurate automated- tracking procedures to generate both 3D trajectories for individual cells and 3D flows for a group of cells. Tracking is currently done independently for each cell, using a cell's image as a template to search for a similar image at the next time point. Finally, sophisticated visualization techniques are needed to view the 3D movies of cell locomotion which are currently viewed simply by 2D projection along a given angle at each time point of the movie.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James G. McNally "Computational optical-sectioning microscopy for 3D quantization of cell motion: results and challenges", Proc. SPIE 2302, Image Reconstruction and Restoration, (30 September 1994); https://doi.org/10.1117/12.188052
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Cited by 7 scholarly publications.
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KEYWORDS
3D image processing

Tissues

Image restoration

Visualization

Image processing

Microscopy

Expectation maximization algorithms

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