normalizeFrames

A <code>Frames</code> object to normalize

frames

The normalization function chosen. Can be one of <code>mean</code> or <code>median</code>

normFun

Applies a transformation to the <code>Frames</code> object in a way that the intensities
throughout the acquisition are normalized overall in term of pixel values sums.
It can be used to compensate for example a global change in the illumination values,
e.g. due to changed acquisition conditions in experiments that span long timescales.

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. 

normalizeFrames: Normalize the values of a `Frames` object

Description

Usage

Arguments

Value

Examples