Stomatal Microtubule Detection Dataset

The dataset is utilized for the application of methods detailed in the paper titled "Segmenting Tubular Structures in Biological Images via Geometry-Aware Stretching Active Curves". Microtubule (MT) images were collected with a Zeiss Axio Observer microscope attached to a Yokogawa CSU-X1 spinning disk head with a 100X objective (1.4 NA, oil immersion). MTs were visualized by tagging TUA5, a component of MTs, with mCherry, a red fluorescent protein. A 561-nm excitation laser and a 593/40 nm emission filter was used. Z-stack images were collected with a step size of 0.2 $\mu{m}$ in Z. To enhance the signal-to-noise ratio, images were first background subtracted and contrast enhanced in ImageJ. The Sliding Paraboloid algorithm with a rolling ball radius of 30 pixels was used for background subtraction. Saturated pixels were set to 0.4 percent for contrast enhancement.

Data and Resources

Additional Info

Field Value
Author Baris Kandemir
Last Updated June 23, 2024, 17:20 (UTC)
Created June 23, 2024, 17:20 (UTC)
Citation Baris Kandemir 2019. Stomatal Microtubule Detection Dataset. CyVerse Data Commons. DOI 10.25739/5g44-hd65
Date created in discovery environment 2019-09-03 04:58:33
Date last modified in discovery environment 2020-02-20 22:05:33
contributor Charles T. Anderson, Yue Rue
fundingReference National Science Foundation MCB 1616316
identifierType DOI
publisher CyVerse Data Commons
resourceType microscopy image dataset