Paper
9 February 2012 Threshold-free method for three-dimensional segmentation of organelles
Yee-Hung M. Chan, Wallace F. Marshall
Author Affiliations +
Abstract
An ongoing challenge in the field of cell biology is to how to quantify the size and shape of organelles within cells. Automated image analysis methods often utilize thresholding for segmentation, but the calculated surface of objects depends sensitively on the exact threshold value chosen, and this problem is generally worse at the upper and lower zboundaries because of the anisotropy of the point spread function. We present here a threshold-independent method for extracting the three-dimensional surface of vacuoles in budding yeast whose limiting membranes are labeled with a fluorescent fusion protein. These organelles typically exist as a clustered set of 1-10 sphere-like compartments. Vacuole compartments and center points are identified manually within z-stacks taken using a spinning disk confocal microscope. A set of rays is defined originating from each center point and radiating outwards in random directions. Intensity profiles are calculated at coordinates along these rays, and intensity maxima are taken as the points the rays cross the limiting membrane of the vacuole. These points are then fit with a weighted sum of basis functions to define the surface of the vacuole, and then parameters such as volume and surface area are calculated. This method is able to determine the volume and surface area of spherical beads (0.96 to 2 micron diameter) with less than 10% error, and validation using model convolution methods produce similar results. Thus, this method provides an accurate, automated method for measuring the size and morphology of organelles and can be generalized to measure cells and other objects on biologically relevant length-scales.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yee-Hung M. Chan and Wallace F. Marshall "Threshold-free method for three-dimensional segmentation of organelles", Proc. SPIE 8225, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues X, 822529 (9 February 2012); https://doi.org/10.1117/12.909278
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Cited by 4 scholarly publications.
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KEYWORDS
Yeast

Image segmentation

Clouds

Luminescence

Microscopes

Spherical lenses

Image analysis

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