shinyFlow

Launches a Shiny Web Application for interactive data exploration. Default data loaded are
the frames from the <code>MesenteriumSubset</code> object, custom values can be inserted by typing
the location of the data stored in a local folder. The Application is structured in a variety
of tabs that mirror the steps in the usual workflow in time-lapse microscopy images. These can
allow the user to interactively explore the parameters and their effect in the reactive
framework provided by Shiny.

flowcatchR is a set of tools to analyze in vivo microscopy imaging
    data, focused on tracking flowing blood cells. It guides the steps from
    segmentation to calculation of features, filtering out particles not of
    interest, providing also a set of utilities to help checking the quality of
    the performed operations (e.g. how good the segmentation was). It allows investigating the 
    issue of tracking flowing cells such as in blood vessels, to categorize the particles in 
    flowing, rolling and adherent. This classification is applied in the study of phenomena such as
    hemostasis and study of thrombosis development. Moreover, flowcatchR presents an integrated 
    workflow solution, based on the integration with a Shiny App and Jupyter notebooks, which is 
    delivered alongside the package, and can enable fully reproducible bioimage analysis in the 
    R environment. 

shinyFlow: Shiny application for exploring the features and parameters provided by `flowcatchR`

Description

Usage

Arguments

Value

Examples