Application Name

Network Formation Assay

Version

3.0.0

Documentation Version

03.12.2024 - 1

Input Image(s)

2D (standard and/or WSI) / Time Series / z-Stack / Multichannel Images; RGB or Grayscale (8 bit)

Input Parameter(s)

Regions of interest (optional)

Keywords

network, tube, formation, in-vitro, angiogenesis, vessel, growth, microscopy, matrigel

Short Description

Detection of branching points, loops, and cell coverage in network formation assay used for in-vitro angiogenesis research.

References / Literature

For more information regarding the assay check e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3230200/;

Reference laboratory: Department of Obstetrics and Gynecology: Dr. Ursula Hiden; Jasmin Strutz, MSc;

2D (standard and/or WSI),

Time Series,

Multichannel,

Z-stack*

Check image format File formats

1 (Greyscale)

3 (RGB)

8 Bit

Standard and WSI:
Max: 8200 x 8200

typically: 1.75

Image content

Microscopy image of 2D network (“tube”) formation assay, typically taken with 4x magnification.

Additional requirements: None

csv

results.csv:

A csv file containing statistics about input image.

csv

results_01_loops.csv:

A csv file containing statistics about detected loops.

csv

results_02_tubes.csv:

A csv file containing statistics about detected tubes.

jpg

results_vis/vis.jpg (2D image, no ROI), or

results_vis/t<time-step>.jpg (time step <time-step> of time series, no ROI), or

results_vis/<roi-id>.jpg (2D image, ROI <roi-id>), or

results_vis/t<time-step>_<roi-id>.jpg (time step <time-step> of time series, ROI <roi-id>):

A visualization of the analysis result for a specific time step for either the whole image (if no inclusion ROIs selected for analysis) or each individual inclusion ROI:

• Branching points are visualized as green circles.

• The skeleton (centerline) of the tubular-structure is shown as a red line.

• The area covered by cells is shown in a color representing its local thickness.
  The colormap for the thickness is displayed below:

  Open

  

• The loops are visualized using different colors and labelled with L followed by the loop id. The loop id corresponds to the id in results_01_loops.csv.

Open

Results visualization

Reference: Dr. Ursula Hiden, Department of Obstetrics and Gynecology, Medical University of Graz; Jasmin Strutz, MSc, Department of Obstetrics and Gynecology, Medical University of Graz

json

annotation_results.json:

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

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.

jpg

rois_visualization.jpg, or

t<time-step>_z<z-layer>_c<channel>_rois_visualization.jpg:

An overview visualization to show locations of all analyzed ROIs for the 2D image or time step <time-step> of a time series, z-layer <z-layer> of a z-stack, or channel <channel> of a multichannel image.

json

jobResultBundleMeta.json:

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

1

t

3

1 - 

Time step, i.e. the position of the image in the time series.

2

z

5

1 - 

z-layer, i.e. the position of the layer in the z-stack.

3

c

2

1 - 

Channel, i.e. the position of the channel in the multichannel image.

4

roi_id

ROI-03

ROI-01 - 

<roi-id> starting from “ROI-01”. Empty, if no inclusion ROI is specified and the whole image was analyzed.

5

roi_name

“central”

text

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

6

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.

7

branching points

104

0 -

Number of detected branching points.

8

covered area [Px^2]

93869

0 - # of pixels in image

Total area covered by cells or tubes in pixels.

9

num_tubes

190

0 -

Number of tubes detected.

10

total_tube_length [Px]

6641.4

0 - # of pixels in image

Total length of all tubes in pixels.

It is calculated by taking the length of the skeleton, which is a simplified representation of its shape. The skeleton can be seen in the visualization.

11

average_tube_length [Px]

34.95

0 - # of pixels in image

Average length of detected tubes in pixels.

12

mean_tube_thickness [Px]

21.268

1-

Average thickness of detected tubes in pixels.

1

t

3

1 - 

Time step, i.e. the position of the image in the time series.

2

z

5

1 - 

z-layer, i.e. the position of the layer in the z-stack.

3

c

2

1 - 

Channel, i.e. the position of the channel in the multichannel image.

4

roi_id

ROI-03

ROI-01 - 

<roi-id> starting from “ROI-01”. Empty, if no inclusion ROI is specified and the whole image was analyzed.

5

roi_name

“central”

text

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

6

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.

7

object_id

1

1 -

Loop id.

8

area [Px^2]

10747

201 - # of pixels in image

Area of the loop in pixels.

9

perimeter [Px]

452.3

0 -

Perimeter of loop in pixels.

1

t

3

1 - 

Time step, i.e. the position of the image in the time series.

2

z

5

1 - 

z-layer, i.e. the position of the layer in the z-stack.

3

c

2

1 - 

Channel, i.e. the position of the channel in the multichannel image.

4

roi_id

ROI-03

ROI-01 - 

<roi-id> starting from “ROI-01”. Empty, if no inclusion ROI is specified and the whole image was analyzed.

5

roi_name

“central”

text

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

6

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.

7

object_id

1

1 -

tube id.

8

tube_thickness [Px]

5.1243

1-

Average thickness of the tube in pixels.

9

tube_type

1

0, 1, 2 or 3

Type of the tube:

0: endpoint-to-endpoint (isolated branch/tube)
1: junction-to-endpoint
2: junction-to-junction
3: isolated cycle

10

tube_length [Px]

452.3

1 -

Length of the tube in pixels.

It is calculated by taking the length of the skeleton, which is a simplified representation of its shape. The skeleton of each tube can be seen in the visualization.