Automated Cell Segmentation for Quantitative Phase Microscopy.

ABSTRACT: Automated cell segmentation and tracking is essential for dynamic studies of cellular morphology, movement, and interactions as well as other cellular behaviors. However, accurate, automated, and easy-to-use cell segmentation remains a challenge, especially in cases of high cell densities, where discrete boundaries are not easily discernable. Here, we present a fully automated segmentation algorithm that iteratively segments cells based on the observed distribution of optical cell volumes measured by quantitative phase microscopy. By fitting these distributions to known probability density functions, we are able to converge on volumetric thresholds that enable valid segmentation cuts. Since each threshold is determined from the observed data itself, virtually no input is needed from the us

SUBMITTER: Loewke NO 

PROVIDER: S-EPMC5907807 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature