Application Name

IKOSA AI Semantic Segmentation App

Version

5.1.0

Documentation Version

06.11.2023 - 1

Input Image(s)

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

RGB or Grayscale (8/16 bit, 16-bit support only if trained with IKOSA AI Trainer version >= 2.3.0)

Input Parameter(s)

Regions of interest (optional)

Keywords

-

Short Description

Segmentation of regions/objects that resemble the appearance of regions/objects annotated and labeled in the training data for this application.

References / Literature

2D (standard and/or WSI),

Time Series,

Multichannel,

Z-stack*

Check image format

File formats

3 (RGB)

1 (Grayscale)

8 Bit

or

16 Bit (Gray, 16-bit support only if trained with IKOSA AI Trainer version >= 2.3.0)

WSI formats: arbitrary

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

arbitrary

Image content

Arbitrary

Additional requirements

None

csv

results.csv

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

csv

results_<xx>_<class-name>.csv

A csv file containing the analysis results for all detected objects of class number <xx> with label name <class-name> (in training data) in the input image or inclusion ROIs.

jpg

results_vis/<xx>_<class-name>_vis.jpg (2D image, no ROI), or

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

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

results_vis/<xx>_<class-name>_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 analysis result for a specific time step (of a time series), z-layer (of a z-stack), or channel (of a multichannel image) for either the whole image (if no inclusion ROIs selected for analysis) or each individual inclusion ROI, for each class number <xx> with label name <class-name> (in training data).

Each visualization includes two parts:

• segmentation

  • predicted regions/objects areas are shown as an overlay in green color.

• objects

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

  • object instance index number corresponds to the object_id as listed in the results_<xx>_<class-name>.csv file.

json

annotation_results.json:

JSON file containing segmented regions. 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 “ROI1”. 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

<class-name>_total_num_objects

3796

0 - 

Total number of detected objects of class <class-name> in ROI or image.

8

<class-name>_on_border_num_objects

12

0 - total_num_objects

Number of objects of class <class-name> which are detected in the image/ROI and touch the border of the image/ROI.

9

<class-name>_holes_num_objects

3

0 - total_num_objects

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

10

<class-name>_recombined_num_objects

4

0 - total_num_objects

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

11

<class-name>_total_area [Px^2]

122438

0 - no. of image px

Total area covered by detected objects of class <class-name> in Pixels^2.

12

<class-name>_total_area [%]

3.66

0 - 100

Total area covered by detected objects of class <class-name> as percentage of overall  image area or ROI area inside the image.

...

Similar to columns 7-12 with further classes.

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 “ROI1”. 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

5

1 - 

ID of object corresponding to id in visualization of ROI or image. More information regarding numbering can be found in Numbering (IDs) of objects in analysis results.

8

is_on_border

“True”

“True” or “False”

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

9

has_holes

“False”

“True” or “False”

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

10

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).

11

area [Px^2]

132

1 -

Area of detected object in Pixels^2.

12

bbox_area [Px^2]

175

1 -

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

13

area_ratio [%]

0.4

0 - 100

Area of detected object as percentage of overall  image area or ROI area inside the image.

14

perimeter [Px]

12.3

0 -

Perimeter of detected object in Pixels.

15

circularity

0.91

0 -

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

16

circularity_ISO

0.65

0 - ~1

Circularity of detected object calculated by ISO definition.

17

solidity

0.98

0 - 1

Ratio of pixels in the region to pixels of the convex hull image.

18

eccentricity

0.96

0 - 1

Eccentricity of the ellipse that has the same second-moments as the region. 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.

19

equivalent_diameter [Px]

10.3

0 -

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

20

extent

0.73

0 - 1

Ratio of pixels in the region to pixels in the total bounding box

21

minor_axis_length [Px]

6

1 -

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

22

major_axis_length [Px]

12

1 -

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