NeuroModex VNet DBS: segmentation and conductivity mapping utilities
Project description
Neuromodex VNet DBS
Deep‑learning utilities for DBS workflows, including MRI brain tissue segmentation (VNet) and conductivity mapping. This repository provides a Python package and optional 3D Slicer modules to integrate the models into imaging workflows.
Features
- VNet‑based multi‑class brain tissue segmentation
- Conductivity mapping utilities
- Pre/post‑processing
- PyTorch inference with automatic device selection (CPU/GPU)
- 3D Slicer plugin scaffolding for GUI‑based use
- The segmentation model was trained using labels generated with ELMA, a semi‑automatic DBS tissue classification/segmentation tool (commonly used to classify tissues such as grey matter, white matter, blood, and CSF for patient‑specific DBS FEM modeling workflows). [1] [2]
Installation
Requirements: Python 3.9+
pip install neuromodex-vnet-dbs
The wheel bundles the neuromodex_vnet_dbs/weights/ directory so the packaged models can load without any extra downloads.
Quick start Segmentation
import SimpleITK as sitk
from neuromodex_vnet_dbs import SegmentationPipeline
# Load an input image (e.g., NIfTI)
img = sitk.ReadImage("/path/to/volume.nii.gz")
# or
img = "path/to/volume.nii.gz"
# Run the segmentation pipeline
pipe = SegmentationPipeline(img) # pass either as string or sitk volume
result = pipe.segment_fast(img) # ~7 seconds
# or this for clearer csf segmentation
result = pipe.segment_gmm_csf(img) # ~1.5 minutes
# The returned object is the segmented image
Quick Start Conductivity Mapping
import SimpleITK as sitk
from neuromodex_vnet_dbs import ConductivityProcessingPipeline
mri_img = sitk.ReadImage("path/to/mri_image.nii.gz")
seg_img = sitk.ReadImage("path/to/seg_image.nii.gz")
pipe = ConductivityProcessingPipeline(seg_img, mri_img)
result = pipe.run()
3D Slicer integration
This repo includes helper scripts and example module folders under slicer/.
These scripts can also be used as CLI tools.
-
To install one or more module folders into your local Slicer profile, run:
python slicer/package_slicer_modules.py python slicer/slicer_install_plugin.pyFollow the prompts to choose the plugin(s) and target Slicer installation. Restart Slicer afterwards.
The plugins can then be found in Segmentation/BrainSegmentation and Electrical Conductivity/ConductivityMapping.
License
This project is licensed under the terms of the MIT License. See the LICENSE file for details.
Citation
If you use this project in your research, please cite the appropriate papers for VNet and any downstream methods you apply. Add your preferred citation format here.
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