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The Wound Healing recipe in Aivia detects wound regions and measures the rate of wound closure over time in scratch assay images. The recipe applies machine learning-based technology for cell segmentation and works for both phase contrast and fluorescence microscopy images.

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Table of Contents

maxLevel	3
exclude	[4]

Parameters and Presets

Parameters

Recipe parameters for Wound Healing and their descriptions are summarized in the table below.

Preset Group	Parameter Name	Max Value	Description
Detection	Background Removal Factor	100	Adjusts the sensitivity of the background removal operation; a lower value will preserve larger objects and more background variations
	Contrast Threshold	255	Adjusts the detection sensitivity on the machine learning-enhanced image; a lower value will detect bigger and more objects
	Fill Holes Size	100,000	Adjusts the maximum size threshold for filling in gaps inside a detected object; a lower value will preserve more holes in the detection
	Smoothing Factor	100	Adjusts the amount of smoothing applied to the outline of the detected objects; a lower value will preserve more of the object's morphological features
Subset Filtering	Min Object Size	1,000,000	Specifies the minimum size of objects to be included in the analysis results based on the area of detected regions

Presets

There are two preset groups in the recipe: Detection and Subset Filtering; each group has three pre-configured parameter grouping groupings to help you get started on the analysis. The default preset values are as follows:

Detection

Parameter Name	Low	Medium	High
Background Removal Factor	60	60	60
Contrast Threshold	85	65	50
Fill Holes Size	10,000	10,000	10,000
Smoothing Factor	10	4	1

Measurements

The Wound Healing recipe generates morphological measurements for the the detected regions. You can add additional measurements to the analysis results by using the Measurement Tool in Aivia. The measurements generated by the recipe are as follows.

Morphological	Summary
Wound area to image size ratio Whole image width Whole image height Wound closure speed Whole image aera Percent area of cells	Whole area (whole series) Wound closure speed (whole series)

Tutorial

Before beginning the tutorial, please download the Wound Healing Demo image. For information on how to select presets or modify parameter values, please refer to the tutorial on how to use the Recipe Console.

Unzip the demo file and load the demo image, WoundHealDemo.tif, into Aivia
In the Recipe Console, click on the Recipe selection dropdown menu and select the Wound Healing recipe
Select the Low preset for the Detection group and the Small preset for the Subset Filtering group
Click the From beginningStart button or press the F4 key on your keyboard to begin applying the recipe to the image

The detected wound region outline will be overlaid on the image.

Results

Multimedia

name	WoundHealDemo_output.mp4
autostart	true

Wound Healing results

Versions Compared

Old Version 4

New Version 5

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