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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

This 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

minLevel	1
maxLevel	53

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 px² or µm²	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

outlines of the detected objects; a lower value will preserve more of the

object

objects'

s

morphological features
Subset Filtering	Min Object Size	0	1,000,000 px² or µm²	Specifies the minimum size of objects to be included in the analysis results based on the

area

areas of the detected regions

Presets

There are two preset groups in the recipe: Detection and Subset Filtering

; each

. Each group has three pre-configured parameter groupings to help you get started on the analysis. The default preset values are as follows:

Subset Filtering

Parameter Name	Small	Medium	Large
Min Object Size	1,000 px² or µm²	10,000 px² or µm²	50,000

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 area Percent area of cells	Whole area (whole series) Wound closure speed (whole series)

px² or µm²

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

“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 Start 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

WoundHealDemo

_output.mp4

Measurements

The Wound Healing recipe generates morphological measurements for the the detected regions. You can add additional measurements to the analysis results with the Measurement Tool in Aivia and view measurement definitions on the Measurement Definitions page. The measurements generated by the recipe are given in the table below.

Morphology	Advanced
Whole Image Area Whole Image Area to Image Size Ratio Wound Closure Speed	Percent Area of Cells Wound Area (Whole Series) Wound Closure Speed (Whole Series)

Versions Compared

Old Version 8

New Version Current

Key

Parameters and Presets

Parameters

Presets

Detection

Subset Filtering

Measurements

Tutorial

Results

Measurements

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