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:

nodeID = slicerio.server.file_load("path/to/Segmentation.seg.nrrd", "SegmentationFile")

If the loaded file is modified then it can be reloaded from the updated file:

slicerio.server.node_reload(id=nodeID)

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_idsfunctions:

# 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})