crop.Frames

frames

cutLeft

cutRight

cutUp

cutDown

Amount of pixels to be cut at all sides. Overrides the single side values

cutAll

Logical, whether to just test the cropping or to actually perform it. Default set to <code>FALSE</code>

testing

Arguments to be passed to <code><a href="/link/display?package=flowcatchR&version=1.6.2" rd-options="" data-mini-rdoc="flowcatchR::display">display</a></code> (e.g. setting the <code>method</code> argument)

Performs cropping on the <code>Frames</code> object, selecting how many pixels should be cut on each side

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. 

Federico Marini

flowcatchR

Tools to analyze in vivo microscopy imaging data focused on
    tracking flowing blood cells

crop.Frames function

Arguments to be passed to <code><a href="display" rd-options="">display</a></code> (e.g. setting the <code>method</code> argument)

crop.Frames: Cut borders of a `Frames` object

Description

Usage

Arguments

Value

Details

Examples