Utilities for 3D Slicer
Project description
slicerio
Python utilities for 3D Slicer interoperability.
The package contains utility functions for reading and writing segmentation files and convenience functions for using 3D Slicer via its web API. More functions will be added in the future.
Installation
Using pip:
pip install slicerio
Examples
Read segmentation and show some information about segments
import slicerio
import json
segmentation_info = slicerio.read_segmentation_info("Segmentation.seg.nrrd")
number_of_segments = len(segmentation_info["segments"])
print(f"Number of segments: {number_of_segments}")
segment_names = slicerio.segment_names(segmentation_info)
print(f"Segment names: {', '.join(segment_names)}")
segment0 = slicerio.segment_from_name(segmentation_info, segment_names[0])
print("First segment info:\n" + json.dumps(segment0, sort_keys=False, indent=4))
Extract selected segments with chosen label values
import slicerio
import nrrd
input_filename = "path/to/Segmentation.seg.nrrd"
output_filename = "path/to/SegmentationExtracted.seg.nrrd"
segment_names_to_labels = [("ribs", 10), ("right lung", 12), ("left lung", 6)]
voxels, header = nrrd.read(input_filename)
extracted_voxels, extracted_header = slicerio.extract_segments(voxels, header, segmentation_info, segment_names_to_labels)
nrrd.write(output_filename, extracted_voxels, extracted_header)
View files in 3D Slicer
The server
module allows using Slicer as a data viewer in any Python environment.
All files are loaded into a single Slicer instance, which eliminates the wait time for application startup
and also allows analyzing, comparing multiple data sets in one workspace. The feature is implemented by using
3D Slicer's built-in Web Server module, which offers data access via a REST API.
For example, an image file can be loaded with the command below. The command starts a new Slicer application instance with the web API enabled.
import os
import slicerio.server
# Load from remote URL
slicerio.server.file_load("https://github.com/rbumm/SlicerLungCTAnalyzer/releases/download/SampleData/LungCTAnalyzerChestCT.nrrd")
# Load from local file
# A Slicer application instance (with Web Server enabled) is automatically started, if it is not running already.
slicerio.server.file_load("path/to/SomeImage.nrrd", slicer_executable=f"{os.environ["LOCALAPPDATA"]}/NA-MIC/Slicer 5.2.0/Slicer.exe")
A segmentation file can be loaded by specifying the SegmentationFile
file type:
slicerio.server.file_load("path/to/Segmentation.seg.nrrd", "SegmentationFile")
Supported file types
- image files (nrrd, nii.gz, ...):
VolumeFile
- segmentation file (.seg.nrrd, nrrd, nii.gz, ...):
SegmentationFile
- model file (.stl, .ply, .vtk, .vtp, .vtu, ...):
ModelFile
- markup file (.mrj.json):
MarkupsFile
- transform file (.tfm, .h5, .txt):
TransformFile
- spreadsheet file (.csv, .tsv):
TableFile
- text file (.txt, .json, ...):
TextFile
- sequence file (.mrb, .seq.nrrd):
SequenceFile
- Slicer scene file (.mrml, .mrb):
SceneFile
Inspect data in 3D Slicer
Metadata of data sets loaded into the server can be obtained using node_properties
function:
properties= slicerio.server.node_properties(name="MRHead")[0]
print(properties["ClassName"])
print(properties["ImageData"]["Extent"])
properties = slicerio.server.node_properties(id=segmentationId)[0]
segments = properties["Segmentation"]["Segments"]
for segmentId in segments:
print(f"Segment name: {segments[segmentId]['Name']} - color: {segments[segmentId]['Color']}")
List of available nodes can be retrieved using node_names
and node_ids
functions:
# Retreve node names of all images
slicerio.server.node_names(class_name="vtkMRMLVolumeNode")
# Retrieve all node IDs
slicerio.server.node_ids(class_name="vtkMRMLVolumeNode")
Nodes can be removed from the workspace:
# Remove node by name
slicerio.server.node_remove(name="MRHead")
# Clear the whole scene
slicerio.server.node_remove()
Export files from 3D Slicer
Data sets created in Slicer (e.g., segmentations, landmark point sets), which can be retrieved by writing into file.
# Save the node identified by `MRHead` node name, uncompressed, into the specified file.
slicerio.server.file_save("c:/tmp/MRHeadSaved.nrrd", name="MRHead", properties={'useCompression': False})
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