New software for automated cilia detection in cells (ACDC).

ABSTRACT:

Background

Primary cilia frequency and length are key metrics in studies of ciliogenesis and ciliopathies. Typically, quantitative cilia analysis is done manually, which is very time-consuming. While some open-source and commercial image analysis software applications can segment input data, they still require the user to optimize many parameters, suffer from user bias, and often lack rigorous performance quality assessment (e.g., false positives and false negatives). Further, optimal parameter combinations vary in detection accuracy depending on cilia reporter, cell type, and imaging modality. A good automated solution would analyze images quickly, robustly, and adaptably-across different experimental data sets-without significantly compromising the accuracy of manual analysis.

SUBMITTER: Lauring MC 

PROVIDER: S-EPMC6670212 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature