TubeTK/Events/2010.09.14: Difference between revisions
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= Meeting topics = | |||
* '''More detailed project brainstorming / thoughts / questions:''' | |||
** Apply slipping-organ motion field regularization to vessel-based registration? | |||
*** Simultaneous registration of multiple vessel trees (e.g. from different organs) with slipping registration? | |||
*** Or combination of vessel-based registration with intensity-based registration? | |||
*** How well do non-rigid registrations based on vessels apply to organ surfaces? | |||
** Likelihood of vessels sliding along each other? | |||
*** Unlikely? | |||
** Discontinuities in 4D image registration, ex. fast changes that look discontinuous due to sampling rate? | |||
*** Smoothing in time? | |||
*** Discontinuous because one organ moves much faster than its neighbor? (ex. heart, lung, etc) | |||
** Non-rigid registration despite occlusions from surgical tools | |||
*** Unobtrusive registration between intraoperative and preoperative images, ex. for registration updates during surgery | |||
*** Ex intraoperative fluoro (both tools and vessels are dark?) (US: tools bright, vessels black) | |||
*** Perhaps rigid registration can overcome tool occlusion, but what to do in non-rigid registration? | |||
**** But how often is non-rigid registration used intraoperatively nowadays? Thinking ahead... | |||
*** Alternative: track tools (tracking system / image-based) and then mask them out so that they are not considered during registration. | |||
**** What would be the advantage to incorporating it into the registration? | |||
*** Or, how well does vessel centerline extraction cope with tools in the field of view? | |||
**** Probably would do ok... tested? (could test artificially) | |||
** Characterizing sliding motion, for additional constraints / anatomically-based strategies | |||
**** already extensively studied for respiration | |||
= Status = | |||
== Danielle == | |||
* built VMTK / Slicer /w VMTK modules | |||
* read Schmidt-Richberg et al., Slipping objects in image registration: Improved motion field estimation with direction-dependent regularization, MICCAI 2009 | |||
* looked over Marc's notes | |||
* brainstorming | |||
== Romain == | |||
* Preliminary results from tumor microenvironment segmentation | |||
* Slicer built with VMTK modules | |||
* Learning execution model of Slicer | |||
* Reviewing papers from Dr. Bullitt on tortuosity | |||
Romain | Romain | ||
Revision as of 17:16, 14 September 2010
Meeting topics
- More detailed project brainstorming / thoughts / questions:
- Apply slipping-organ motion field regularization to vessel-based registration?
- Simultaneous registration of multiple vessel trees (e.g. from different organs) with slipping registration?
- Or combination of vessel-based registration with intensity-based registration?
- How well do non-rigid registrations based on vessels apply to organ surfaces?
- Likelihood of vessels sliding along each other?
- Unlikely?
- Discontinuities in 4D image registration, ex. fast changes that look discontinuous due to sampling rate?
- Smoothing in time?
- Discontinuous because one organ moves much faster than its neighbor? (ex. heart, lung, etc)
- Non-rigid registration despite occlusions from surgical tools
- Unobtrusive registration between intraoperative and preoperative images, ex. for registration updates during surgery
- Ex intraoperative fluoro (both tools and vessels are dark?) (US: tools bright, vessels black)
- Perhaps rigid registration can overcome tool occlusion, but what to do in non-rigid registration?
- But how often is non-rigid registration used intraoperatively nowadays? Thinking ahead...
- Alternative: track tools (tracking system / image-based) and then mask them out so that they are not considered during registration.
- What would be the advantage to incorporating it into the registration?
- Or, how well does vessel centerline extraction cope with tools in the field of view?
- Probably would do ok... tested? (could test artificially)
- Characterizing sliding motion, for additional constraints / anatomically-based strategies
- already extensively studied for respiration
- Apply slipping-organ motion field regularization to vessel-based registration?
Status
Danielle
- built VMTK / Slicer /w VMTK modules
- read Schmidt-Richberg et al., Slipping objects in image registration: Improved motion field estimation with direction-dependent regularization, MICCAI 2009
- looked over Marc's notes
- brainstorming
Romain
- Preliminary results from tumor microenvironment segmentation
- Slicer built with VMTK modules
- Learning execution model of Slicer
- Reviewing papers from Dr. Bullitt on tortuosity
Romain
Read Noise Reduction in Computed Tomography Scans Using 3-D Anisotropic Hybrid Diffusion With Continuous Switch.
Running the itk anisotropic filters tests