Application Name

Version

2.2.0

Documentation Version

19.12.2023 - 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

spheroid, sprouting, sprout, formation, in-vitro, angiogenesis, vessel, growth, microscopy

Short Description

Detection and quantification of sprouts in a spheroid capillary sprouting assay used for in-vitro angiogenesis research.

References / Literature

For more information regarding the assay check e.g. https://www.ncbi.nlm.nih.gov/pubmed/23911327;

2D (standard and/or WSI),

Time Series,

Multichannel,

Z-stack*

Check image format File formats

3 RGB or

1 Grayscale

8 Bit

Standard and WSI:

Min: 10 x 10

Max: 6,144 x 6,144

typically: 0.3 - 0.7

Image content

Transmitted light or phase contrast microscopy image of spheroid capillary sprouting assay, typically taken with 10x magnification. In case of multiple bodies in the image, the body closest to the image/ROI center is detected and used for sprout analysis.

Additional requirements: None

csv

results.csv:

A csv file containing the analysis results for the input image.

csv

results_01_sprouts.csv:

A csv file containing the morphometric parameters of the detected sprouts.

jpg

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

results_vis/t<time-step>_z<z-layer>_c<channel>.jpg (for time series, z-stack, or multichannel image, no ROI), or

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

results_vis/t<time-step>_z<z-layer>_c<channel>_<roi-id>.jpg (for time series, z-stack, or multichannel image, ROI <roi-id>):

A visualization of the detection.

• The segmented body is shown in yellow, different sprouts are shown in different other colors.

• The skeleton, which is used to calculate the sprouting length, is shown in red.

• Sprouts are labelled with white numbers that correspond to the numbers given in results_01_sprouts.csv.

• In case of multiple bodies in the image/ROI, the body closest to the image/ROI center is detected and used for sprout analysis

Open

Results visualization

Open

Input image

Reference: Dr. Ingeborg Klaassen, Ocular Angiogenesis Group, Department Ophthalmology, Amsterdam UMC

json

annotation_results.json:

JSON file containing detected body and sprouts. 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

number_of_sprouts

26

0 - 

Number of detected sprouts.

8

sprouts_total_length [Px]

1004

0 -

Total length of all sprouts in pixels.

9

sprouts_total_area [Px^2]

3756

0 - 

Total area of all sprouts in pixels^2.

10

body_area [Px^2]

58775

0 -

Area of body in pixels^2.

11

body_circularity

0.76

0 - 1

Circularity of the body calculated as

where A denotes the area of the body and P the perimeter of the body.

Note: Due to the discrete nature of images, the calculation of the perimeter can only be approximated. Therefore, the circularity of a body being a circle, results in a value of approximately 0.9. Theoretically, a circle has a value of 1.0. [1]

[1] Bottema, Murk J. "Circularity of objects in images." 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No. 00CH37100). Vol. 4. IEEE, 2000.