Difference between revisions of "2010 Winter Project Week Spine Segmentation Module in Slicer3"

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Image:spine_segmentation_module_in_slicer_001.png|Our segmentation algorithm has been integrated into Slicer 3.5. ([http://www.youtube.com/watch?v=kkAuP80kE8E See a video])
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Image:spine_segmentation_module_in_slicer_001.png|Our goal is to develop a Slicer module to automatically segment the spine in 3D MRI images to help during the surgical removal of herniated discs. ([http://www.youtube.com/watch?v=kkAuP80kE8E See a video])
Image:spine_segmentation_module_in_slicer_002.png|Results of the SpineSegmentation module in Slicer 3.5
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Image:spine_segmentation_module_in_slicer_002.png|The cause of back pain is the pressure of the herniated disc onto the spinal nerves. This Slicer rendering shows an herniated disc pushing the canal where the cerebro-spinal fluid (CSF) needs to insulate the nerves from outside shocks.
Image:spine_segmentation_in_slicer_004.png|3D meshes of our automated segmentation results
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Image:spine_segmentation_in_slicer_004.png|Surface meshes and volumetric meshes of our automatically created model of the CSF. The paths where the nerves exit the spine appear as two roots descending on each side of the spinal column.
Image:Jaume_Loepprich_vertebrae_3D_rendering.png|Model of a lumbar vertebrae for our shape-based segmentation algorithm. This complex shape is detected across the volumetric image following an automated pattern recognition approach
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Image:Jaume_Loepprich_vertebrae_3D_rendering.png|A complex model of a lumbar vertebrae has been created to drive our shape-based segmentation algorithm in a robust and accurate recognition. This volumetric pattern recognition algorithm is fully implemented as a Slicer module using ITK and VTK.
 
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Revision as of 06:10, 21 January 2010

Home < 2010 Winter Project Week Spine Segmentation Module in Slicer3

Key Investigators

  • Sylvain Jaume (MIT)
  • Martin Loepprich (University of Heidelberg)
  • Ron Kikinis, Steve Pieper (BWH)
  • Polina Golland (MIT)

Objective

We are developing a Slicer module to segment the region within the thecal sac in MRI images of the spine. Our objective is to provide a segmentation and visualization tool to improve the treatment of disc herniation. The structures of interests are the cerebro-spinal fluid (CSF), the discs, the vertebrae and the spinal nerves. The main challenge is to perform the segmentation in a fully automated way.

Approach, Plan

Our plan for the project week is to integrate our code into Slicer 3.5. Our code analyzes the intensity profile of different regions in the MRI and automatically defines the optimum region for the CSF.

Progress

The algorithm has been implemented in Slicer 3.5 as an extension module. The code is organized as ITK and VTK classes. No interaction is required. The module has been tested on data sets acquired at Brigham and Women's Hospital using the Wideband Steady-State Free-Precession (WB-SSFP) MRI protocol [Krishna Nayak 2007].

Screenshots

Results of the SpineSegmentation module in Slicer 3.5
Results of the SpineSegmentation module in Slicer 3.5
Double cylinder used for our model-based.
Results of our automated nerve segmentation algorithm. The 3D rendering shows the nerves exiting the spinal cord and the ganglia
Intensity profile for the cross-section of a nerve. The MRI image was acquired using the wideband steady-state free-precession (WB-SSFP) protocol.
Organization of the source code for the SpineSegmentation module. This module is available as an extension module for Slicer 3.5.


References

  • Segmentation using Slicer 3.5, EMSegment module