Difference between revisions of "2008 IGT Project Week Nonrigid MR-ULS Registration Algorithms for Neurosurgery, Prostate MRgFUS and Brachytherapy"
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Back to [[2008_IGT_Project_Week#Projects]] | Back to [[2008_IGT_Project_Week#Projects]] | ||
+ | Team: Sandy Wells, Tina Kapur, Matt Toews, Ben Schwartz, Steve Haker, Michel Audette, Andinet E, Ziv Yanivm Jay, John Onofrey, Raul San Jose | ||
− | + | [[Media:2008_IGT_Project_Week_Registration.ppt|Powerpoint Presentation]] | |
− | Goals: | + | Goals: |
− | + | A round table discussion of issues relating to multimodal (MR/CT-US) registration for image-guided therapy. This will include: | |
− | + | #Definition of relevant research issues | |
− | + | #Visual Inspection of data sets brought by participants | |
− | + | #Discussion of clinical requirements for the three focus applications: Neurosurgery, Prostate MRgFUS, and Prostate Brachytherapy, Image Guided Endoscopy/Laproscropy | |
+ | #Where available, identification of particular algorithms for each of the focus applicatons | ||
− | + | Non-exhaustive List of Issues for Discussion | |
− | + | #Goals of Non-Rigid MR-US Registration? | |
− | + | #*Use coarse, cost-effective inter-operative US imagery to update detailed preoperative MR imager, to enhance visualization during therapy. | |
− | + | #Requirements | |
+ | #*Clinical requirements: registration precision? | ||
+ | #*Is MR-US registration necessary? | ||
+ | #State-of-the-art | ||
+ | #*Existing systems? | ||
+ | #*Real-time? | ||
+ | #*Accuracy? | ||
+ | #Image Registration | ||
+ | #*MR-US similarity measurement: mutual information, correlation ratio? | ||
+ | #*Transforms: rigid, deformable? Outlier detection? | ||
+ | #*3DMR-2DUS slices? 3DMR-3DUS? 3DMR-3DUS reconstuction? | ||
+ | #*Initialialization: 3D tracking of US probe? | ||
+ | #*Freehand US? | ||
+ | #*Robust? | ||
+ | #Updating Pre-operative Imagery | ||
+ | #*What information is required? Rigid/non-rigid deformation? Resolution? | ||
+ | #*Interpolation? | ||
+ | #Challenges | ||
+ | #*Poor US image quality, occlusion, resection, poor visibility of anatomy | ||
+ | #*Computational complexity | ||
+ | #Data | ||
+ | #*Phantom data? | ||
+ | #*Data sharing for benchmarking? | ||
+ | #Approach-based path planning | ||
+ | #*Neurosurgical guidance can/should integrate knowledge of surgical approach: frontal, occipital, pterional, transnasal... | ||
+ | #* Use knowledge of _specific_ critical tissues & likely eloquent areas in path planning | ||
+ | #* Curvilinear neurosurgical path planning. |
Latest revision as of 15:11, 9 December 2008
Home < 2008 IGT Project Week Nonrigid MR-ULS Registration Algorithms for Neurosurgery, Prostate MRgFUS and BrachytherapyBack to 2008_IGT_Project_Week#Projects
Team: Sandy Wells, Tina Kapur, Matt Toews, Ben Schwartz, Steve Haker, Michel Audette, Andinet E, Ziv Yanivm Jay, John Onofrey, Raul San Jose
Goals: A round table discussion of issues relating to multimodal (MR/CT-US) registration for image-guided therapy. This will include:
- Definition of relevant research issues
- Visual Inspection of data sets brought by participants
- Discussion of clinical requirements for the three focus applications: Neurosurgery, Prostate MRgFUS, and Prostate Brachytherapy, Image Guided Endoscopy/Laproscropy
- Where available, identification of particular algorithms for each of the focus applicatons
Non-exhaustive List of Issues for Discussion
- Goals of Non-Rigid MR-US Registration?
- Use coarse, cost-effective inter-operative US imagery to update detailed preoperative MR imager, to enhance visualization during therapy.
- Requirements
- Clinical requirements: registration precision?
- Is MR-US registration necessary?
- State-of-the-art
- Existing systems?
- Real-time?
- Accuracy?
- Image Registration
- MR-US similarity measurement: mutual information, correlation ratio?
- Transforms: rigid, deformable? Outlier detection?
- 3DMR-2DUS slices? 3DMR-3DUS? 3DMR-3DUS reconstuction?
- Initialialization: 3D tracking of US probe?
- Freehand US?
- Robust?
- Updating Pre-operative Imagery
- What information is required? Rigid/non-rigid deformation? Resolution?
- Interpolation?
- Challenges
- Poor US image quality, occlusion, resection, poor visibility of anatomy
- Computational complexity
- Data
- Phantom data?
- Data sharing for benchmarking?
- Approach-based path planning
- Neurosurgical guidance can/should integrate knowledge of surgical approach: frontal, occipital, pterional, transnasal...
- Use knowledge of _specific_ critical tissues & likely eloquent areas in path planning
- Curvilinear neurosurgical path planning.