Difference between revisions of "2017 Winter Project Week/LORDWI"

Latest revision as of 15:45, 13 January 2017

Objective	Approach and Plan	Progress and Next Steps
Objective: Evaluate/validate a density-based non-rigid registration framework for DWI (see the link below for a paper on similarity measure used). In short: Is this a good registration? Short description: The model is based on Free-Form Deformation B-splines where the diffusion gradient directions are updated using the normalized Jacobian. B-spline interpolation is used spatially, the Watson Distribution is used (gradient) directionally. Histogram is smoothed. Similarity is NMI and optimisation is L-BFGS.	Discuss best ways to validate results (tractography, biomarkers, synthetic data, phantoms, others?). So far we have visually tested inter-subject registrations of HCP data, intra-subject multi-shell, and intra-subject on child brain tumor subjects. Figure out anyone is in need of DWI registration for testing, have a dataset already registered (for comparison), or can help with anatomical landmarks. Consider if Slicer can be used in tandem for evaluation.	The goal was too lofty but the week was excellent. Had a lot of great discussions and good insight into what others are doing. Got working on acquiring data from different sources (more problems are always welcome!) Shared some experiences. Got a nice introduction to Slicer.

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 * Figure out anyone is in need of DWI registration for testing, have a dataset already registered (for comparison), or can help with anatomical landmarks.
 * Consider if Slicer can be used in tandem for evaluation.
-* This method introduces Mutual Information to nonrigid registration of DWI. Discuss if other similarity measures (e.g. correlation measures) would be better suited for specific problems.
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 <!-- Progress and Next steps bullet points (fill out at the end of project week) -->
-*
+The goal was too lofty but the week was excellent.
+* Had a lot of great discussions and good insight into what others are doing.
+* Got working on acquiring data from different sources (more problems are always welcome!)
+* Shared some experiences.
+* Got a nice introduction to Slicer.
 |}