Segmentation_Values_Testing 1.0
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Run on GalaxyWorkflow to assess nuclei segmentation by applying different Gaussian filtering values during image pre-processing.
Associated Tutorial
This workflows is part of the tutorial Parameter tuning and optimization - Evaluating nuclei segmentation with Galaxy, available in the GTN
Features
- Includes Galaxy Workflow Tests
- Includes a Galaxy Workflow Report
- Uses Galaxy Workflow Comments
Thanks to...
Workflow Author(s): Riccardo Massei
Tutorial Author(s): Riccardo Massei
Tutorial Contributor(s): Leonid Kostrykin, Beatriz Serrano-Solano, Riccardo Massei
Funder(s): Deutsche Forschungsgemeinschaft
Grants(s): NFDI4Bioimage
Inputs
| ID | Name | Description | Type |
|---|---|---|---|
| Ground Truth Image | Ground Truth Image | Input the ground truth image |
|
| Image to segment | Image to segment | Upload an image or provide a dataset to initiate the image segmentation process. |
|
| Sigma Values | Sigma Values | Input a series of sigma values as tabular file |
|
Steps
| ID | Name | Description |
|---|---|---|
| 3 | Split by group | toolshed.g2.bx.psu.edu/repos/bgruening/split_file_on_column/tp_split_on_column/0.6 |
| 4 | Parse parameter value | param_value_from_file |
| 5 | Filter 2-D image | toolshed.g2.bx.psu.edu/repos/imgteam/2d_simple_filter/ip_filter_standard/1.12.0+galaxy1 |
| 6 | Perform histogram equalization | toolshed.g2.bx.psu.edu/repos/imgteam/2d_histogram_equalization/ip_histogram_equalization/0.18.1+galaxy0 |
| 7 | Threshold image | toolshed.g2.bx.psu.edu/repos/imgteam/2d_auto_threshold/ip_threshold/0.18.1+galaxy3 |
| 8 | Compute image segmentation and object detection performance measures | toolshed.g2.bx.psu.edu/repos/imgteam/segmetrics/ip_segmetrics/1.4.0-2 |
| 9 | Collapse Collection | toolshed.g2.bx.psu.edu/repos/nml/collapse_collections/collapse_dataset/5.1.0 |
Outputs
| ID | Name | Description | Type |
|---|---|---|---|
| output | output | n/a |
|
Version History
master
Creators and Submitter
Views: 1152 Downloads: 161 Runs: 0
Created: 2nd Jun 2025 at 10:56
AttributionsNone
Related items
Teams: Galaxy Training Network
Organizations: Galaxy
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