title: Integrating image analysis algorithms in a web interface for the quantification of microtubule dynamics.
abstract: We present improvements to a web interface and an integrated computational tracking algorithm for quantitative analysis of microtubule dynamics in live-cell microscopy images. Based on a previously implemented system, more new functionalities have been added to the interface. The system also integrates a computational tracking algorithm to aid the analysis. The analysis workflow of the proposed interface is made similar to the current manual analysis workflow in order to make the interface intuitive to use. We show the workflow of the computer analysis algorithm and how it is used to aid the existing analysis workflow. We also demonstrate how to re-evaluate existing data in a case study using real imaging data. Lastly, we show the added functionalities of the interface including how to share image data and analysis results.
authors.affiliation: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA. kykong@gatech.edu
authors.forename: Koon Yin
authors.initials: KY
authors.lastname: Kong
authors.forename: Adam I
authors.initials: AI
authors.lastname: Marcus
authors.forename: Paraskevi
authors.initials: P
authors.lastname: Giannakakou
authors.forename: May Dongmei
authors.initials: MD
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D020407:Internet; D008856:Microscopy, Fluorescence / Q000379:methods; D008870:Microtubules / Q000378:metabolism*; D014584:User-Computer Interface; D057188:Workflow