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Application Name

Axon Quantification

Version

3.0.0

Documentation Version

30.01.2024 - 1

Input Image(s)

2D (standard and/or WSI); RGB

Input Parameter(s)

Regions of interest (optional)

Keywords

axon, nerve, neuro, peripheral nerve defect, neuroregeneration, regeneration, ex-vivo, trauma, microscopy

Short Description

Detection and quantification of axons in histological sections of peripheral nerves stained with NF200.

References / Literature

Reference laboratory: Ludwig Boltzmann Institute for Experimental and Clinical Traumatology: Mag.rer.nat. Dr. David Hercher; https://trauma.lbg.ac.at/

Table of contents

Table of Contents
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IKOSA Prisma Axon Quantification

You can use this image analysis application or any of our other applications in your account on the IKOSA platform. If it is not on the list of available applications, please contact your organization's administrator or our team at support@kmlvision.com.

Application description

This application automatically segments the neurofilament-positive axons in histological sections of peripheral nerves stained with NF200. Number, area, circumference, roundness/elongation and diameter estimations of the axons are automatically calculated. The application was trained and tested with samples showing peripheral nerves in a rodent (rat) model of neurotmesis (front and hind limbs, proximal of defect, in nerve interponate and distal of defect).

In the following sections, we provide the necessary input data requirements that are necessary to obtain accurate image analysis results and a description of the output files.

Input data requirements

Input image(s)

Input for this application is the following image data:

Image type

Color channels

Color depth (per channel)

Size (px)

Resolution (μm/px)

2D (standard and/or WSI)

Check image format File formats

3 (RGB)

8 Bit

WSI formats: arbitrary

Standard images: max. 25,000 x 25,000


typically: 0.37 - 0.62

Image content

Scan of histological  section(s) showing neurofilament-positive axons of rodent (rat) peripheral nerves stained with NF200 (axons appear as brown/reddish objects), typically taken with 20x magnification.

Additional requirements: None

Note

Important:

For all images, the following requirements apply:

  • The illumination must be constant throughout the image(s).

  • The sample must be in focus, i.e. no blurry regions in image(s).

Input parameter(s)

No additional input parameters are required for this application.

As an optional parameter, a single or multiple regions of interest (ROIs) can be defined in which the analysis should be performed (‘inclusion ROIs’).

Description of output files and their content

Files

File format

Description

1

csv

results.csv:

A csv file containing the overall analysis results for the input image or all inclusion ROIs.

2

csv

results_01_axons.csv:

A csv file containing the analysis results for all detected axons in the input image or inclusion ROIs.

3

jpg

results_vis/vis.jpg (no ROI)or results_vis/<roi-id>.jpg:

A visualization of the analysis result for either the whole image (if no inclusion ROIs selected for analysis) or each individual inclusion ROI. The visualization includes two parts:

  • segmentation

    • predicted axon areas are shown as an overlay in green color.

  • objects

    • axon instances are shown as an overlay in random color.

    • axon instance index number corresponds to the object_id as listed in the results_01_axons.csv file.

Reference: Dr. David Hercher, Ludwig Boltzmann Institute for Experimental and Clinical Traumatology

Info

Please note: These files are only created if qualitative result visualization was requested when submitting the analysis job.

Info

Please note: the image quality might be reduced for the presentation in the technical docs.

4

json

annotation_results.json:

JSON file containing detected axons. The position is measured from the left upper corner (1,1) of the image.

5

json

roiMeta.json:

A json file containing all information regarding the ROIs defined for the analysis job to ensure reproducibility. Also, information regarding image and analysis dimensions is provided.

6

jpg

rois_visualization.jpg:

An overview visualization to show locations of all analyzed ROIs

Info

Please note: This file is only created, if inclusion ROIs were defined for analysis.

7

json

jobResultBundleMeta.json:

A json file containing all information regarding the analysis job (application name and version, project, etc.) to ensure reproducibility

Info

Please note: This file is only included, if bundled or merged analysis jobs are downloaded.

Info

Please note:

  • In the case of inclusion ROIs that are partially outside of the image, the ROIs are cropped to the areas that lie inside the image.

  • In the case of inclusion ROIs that are completely outside of the image, no analysis is performed. However, they are still listed in corresponding results files.

  • A <roi-id> is generated automatically by the application corresponding to the creation date of a ROI. The location of a ROI within an image with its specific <roi-id> can be seen in the file “rois_visualization.jpg.” ROIs that are completely outside of the image are not shown in this file.

  • All visualizations are downscaled to 25 megapixels (MP), if the original image or inclusion ROI is larger than 25 MP.

Content

results.csv

Single csv-file

If one or more ROIs were specified, the results in a specific row refer to the ROI specified in the first columns, otherwise (empty ROI columns) the results refer to the whole image.

Column NO.

Column name

Examples

Value range

Description

1

roi_id

ROI-03

ROI-01 - 

<roi-id> starting from “ROI1”. Empty, if no inclusion ROI is specified and the whole image was analyzed.

2

roi_name

“central”

text

Custom text to identify the ROI. Empty, if no inclusion ROI is specified and the whole image was analyzed.

3

roi_size [Px^2]

1212212

1 -

Size of the ROI that was analyzed in pixels^2. The size of the whole image is given if no inclusion ROI is specified and the whole image was analyzed.

4

on_border_num_objects

12

0 - total_num_objects

Number of objects which are detected in the image/ROI and touch the border of the image/ROI.

5

holes_num_objects

3

0 - total_num_objects

Number of objects which are detected in the image/ROI and have holes (>=1 pixel).

6

recombined_num_objects

4

0 - total_num_objects

Number of objects which are detected at tile borders of image (tile size: 2048x2048 pixels) and are recombined.

7

axons_total_area [Px^2]

122438

0 - no. of image px

Total area covered by detected axons in Pixels^2.

8

axons_total_area [%]

3.66

0 - 100

Total covered by detected axons area as percentage of overall  image area or ROI area inside the image.

9

axons_total_nr_of_objects

3796

0 - 

Total number of detected axons in ROI or image.

results_01_axons.csv

Single csv-file

If one or more ROIs were specified, the results in a specific row refer to the ROI specified in the first columns, otherwise (empty ROI columns) the results refer to the whole image.

Column NO.

Column name

Examples

Value range

Description

1

roi_id

ROI-03

ROI-01 - 

<roi-id> starting from “ROI1”. Empty, if no inclusion ROI is specified and the whole image was analyzed.

2

roi_name

“central”

text

Custom text to identify the ROI. Empty if no inclusion ROI is specified and the whole image was analyzed.

3

roi_size [Px^2]

1212212

1 -

Size of the ROI that was analyzed in pixels^2. The size of the whole image is given if no inclusion ROI is specified and the whole image was analyzed.

4

object_id

5

1 - 

ID of axon corresponding to id in visualization of ROI or image

5

is_on_border

“True”

“True” or “False”

Boolean indicator to show if object is touching the border of the image/ROI.

6

has_holes

“False”

“True” or “False”

Boolean indicator to show if object has holes (>=1 pixel).

7

is_recombined

“False”

“True” or “False”

Boolean indicator to show if object was recombined because it was detected at tile borders of image (tile size: 2048x2048 pixels).

8

area [Px^2]

132

0 -

Area of detected axon in Pixels^2.

9

bbox_area [Px^2]

304

8 -

Area of bounding box of detected object in pixels^2.

10

area_ratio [%]

0.02

0 - 100

Area of detected object as percentage of overall image area or ROI

11

perimeter [Px]

12.3

0 -

Perimeter of detected axon in Pixels.

12

elongation

4.21

0 -

Elongation factor according to the method by https://doi.org/10.1007/s10851-007-0039-0.

13

circularity

0.91

Circularity factor of detected axon; circularity = 4*pi*area/(perimeter^2). The circularity of a circle is 1.

14

circularity

0.78

0 - ~1

Circularity of detected object.

Circularity = 4*pi*area/(perimeter^2).

The circularity of a circle is 1.

1514

circularity_ISO

0.65

0 - ~1

Circularity of detected object

1615

solidity

0.97

0 - 1

Solidity of detected object.

Solidity is calculated out of the ratio of an object’s area to the area of its convex hull.

1716

eccentricity

0.92

0 - 1

Eccentricity of detected object.

Eccentricity of the ellipse that has the same second-moments as the object area. The eccentricity is the ratio of the focal distance (distance between focal points) over the major axis length. When it is 0, the ellipse becomes a circle.

1817

maximum_feret_diameter [Px]

13.6

0 - 

Maximum Feret’s diameter, computed as the longest distance between points around a region’s convex hull contour.

1918

mean_diameter [Px]

8.2

0 -

Mean diameter of object which is computed by the object's area divided by the maximum Feret's diameter.

2019

mean_diameter_ circle [Px]

10.3

0 -

Diameter of a circle having the same area as the detected object.

2120

extent

0.57

0 - 1

Extent of detected object.

The extent value is the ratio of the object area to the total bounding box area.

2221

minor_axis_length [Px]

9

1 -

Minor axis length of detected object.

The minor axis length is the length of the minor axis of the ellipse that has the same normalized second central moments as the object.

2322

major_axis_length [Px]

23

1 -

Major axis length of detected object.

The major axis length is the length of the major axis of the ellipse that has the same normalized second central moments as the object.

Info

Please note: The parameters marked with an asterisk (*) are calculated using https://scikit-image.org/.

Error information

More information about errors can be found in the Application Error Documentation.

Contact

If you have any questions about this app, as well as suggestions or ideas for new ones, email us at support@kmlvision.com.

Feel free to book a 30-minute meeting to speak with us about IKOSA and the apps!

https://calendly.com/kmlvision/book-the-ikosa-platform-demo