Add DICOM support (#1014)

* Add pims dicom reader, testdata and test for reading the dicom file.

* Run formatter.

* Use bioformats instead of dicom reader and add example in docs.

* Add list of suffixes supported by bioformats.

* Add test cassette for upload dicom example.

* Update changelog.

* Update test cassette for upload dicom stack example.

* Update webknossos/webknossos/dataset/_utils/pims_images.py

Co-authored-by: Tom Herold <[email protected]>

---------

Co-authored-by: Tom Herold <[email protected]>

Author: markbader

docs/mkdocs.yml

@@ -90,6 +90,7 @@ nav:
           - Dataset Examples:
               - webknossos-py/examples/dataset_usage.md
               - webknossos-py/examples/upload_tiff_stack.md
+              - webknossos-py/examples/upload_dicom_stack.md
               - webknossos-py/examples/upload_image_data.md
               - webknossos-py/examples/create_dataset_from_images.md
               - webknossos-py/examples/image_stack_to_dataset.md

docs/src/webknossos-py/examples/upload_dicom_stack.md

@@ -0,0 +1,9 @@
+# Upload DICOM stack
+
+To convert a DICOM image stack to a WEBKNOSSOS dataset and upload it to [webknossos.org](https://webknossos.org) the bioformats reader is necessary. This example shows how to [create a new dataset from a dicom sequence](../../api/webknossos/dataset/dataset.md#Dataset.from_images), [compress](../../api/webknossos/dataset/dataset.md#Dataset.compress) it and [upload](../../api/webknossos/dataset/dataset.md#Dataset.upload) it to WEBKNOSSOS.
+
+```python
+--8<--
+webknossos/examples/upload_dicom_stack.py
+--8<--
+```

webknossos/Changelog.md

@@ -16,6 +16,7 @@ For upgrade instructions, please check the respective _Breaking Changes_ section
 
 ### Added
 - Add CLI tool for offline merging of zip annotations with fallback datasets. [#996](https://github.com/scalableminds/webknossos-libs/pull/996)
+- Added support for converting new file formats such as DICOM, using the bioformats reader. [#1014](https://github.com/scalableminds/webknossos-libs/pull/1014)
 
 ### Changed
 - The rules for naming the layers have been tightened to match the allowed layer names on webknossos. [#1016](https://github.com/scalableminds/webknossos-libs/pull/1016)

webknossos/README.md

@@ -51,3 +51,4 @@ Excerpts for testing purposes have been sampled from:
 * Dow Jacobo Hossain Siletti Hudspeth (2018). **Connectomics of the zebrafish's lateral-line neuromast reveals wiring and miswiring in a simple microcircuit.** eLife. [DOI:10.7554/eLife.33988](https://elifesciences.org/articles/33988)
 * Zheng Lauritzen Perlman Robinson Nichols Milkie Torrens Price Fisher Sharifi Calle-Schuler Kmecova Ali Karsh Trautman Bogovic Hanslovsky Jefferis Kazhdan Khairy Saalfeld Fetter Bock (2018). **A Complete Electron Microscopy Volume of the Brain of Adult Drosophila melanogaster.** Cell. [DOI:10.1016/j.cell.2018.06.019](https://www.cell.com/cell/fulltext/S0092-8674(18)30787-6). License: [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)
 * Bosch Ackels Pacureanu et al (2022). **Functional and multiscale 3D structural investigation of brain tissue through correlative in vivo physiology, synchrotron microtomography and volume electron microscopy.** Nature Communications. [DOI:10.1038/s41467-022-30199-6](https://www.nature.com/articles/s41467-022-30199-6)
+* Hanke, M., Baumgartner, F. J., Ibe, P., Kaule, F. R., Pollmann, S., Speck, O., Zinke, W. & Stadler, J. (2014). **A high-resolution 7-Tesla fMRI dataset from complex natural stimulation with an audio movie. Scientific Data, 1:140003.** [DOI:10.1038/sdata.2014.3](http://www.nature.com/articles/sdata20143)

webknossos/examples/upload_dicom_stack.py

@@ -0,0 +1,22 @@
+from pathlib import Path
+from time import gmtime, strftime
+
+import webknossos as wk
+
+
+def main() -> None:
+    time_str = strftime("%Y-%m-%d_%H-%M-%S", gmtime())
+    dataset = wk.Dataset.from_images(
+        str(Path(__file__).parent.parent / "testdata" / "dicoms"),
+        f"dicom_dataset_{time_str}",
+        voxel_size=(12, 12, 12),
+    )
+    dataset.compress()
+
+    remote_dataset = dataset.upload()
+    url = remote_dataset.url
+    print(f"Successfully uploaded {url}")
+
+
+if __name__ == "__main__":
+    main()