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Analysis and processing of Diffusion Weighted MRI. Remco Duits Anna Vilanova Luc Florack. Tom Dela Haije Rutger Fick. Supervised by : Collaboration : with. Overview of presentation. Short introduction to DW-MRI Enhancement of DW-MRI data Fiber tracking. Diffusion of water.
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Analysis and processing of DiffusionWeighted MRI Remco Duits Anna Vilanova Luc Florack Tom Dela Haije Rutger Fick Supervisedby: Collaboration: with
Overview of presentation Short introduction to DW-MRI Enhancement of DW-MRI data Fiber tracking
Diffusion of water Diffusion is dependentonorientation
Overview Water Diffusion Modelling Fiber PDF Tensor(s) Raw Data Water PDF Fiber Tracking Low signal for high diffusion Other models Clinical Information
ConstrainedSphericalDeconvolution Constrained SphericalDeconvolution Original data (single fiber) SphericalDeconvolution
Enhancement of PDFs • PDFs contain information on the direction of water diffusion (water PDF) or fiber distribution (fiber PDF) • Many models canbeconverted to a PDF - Oftennoisy and incoherent
Rotatingcoordinate system z y x diffusion diffusion
Evolutions in new frame Contour Enhancement Contour Enhancement
Evolutions in new frame Contour completion Contour Completion
Resultsonsimplefibertracking Fibertrackingon CSD Fibertracking on enhanced CSD Phantom dataset from the ISBI reconstructionchallenge (2013)
Fiber Tracking • Problem: findanatomical fibers basedon DW-MRI scan • Variants • Findbrain fiber betweentwo areas • Find all fibers that pass throughanarea • Mathematicalproblem? • Multiple options
Local fiber tracking Streamlinetracing: • Compute main direction of diffusion (AKA: reduce to vectorfield: ) • Integratealongvectorfieldfromgivenseedpoint
Advantages/Disadvantages • Advantages • Computationallycheap • Easy to implement • Disadvantages • Erroraccumulation • Sensitive to noise
Global fibertracking • curve Curvature • Corresponding energy functional Solvedfor C(x)=1 Externalcost (data) Geodesicenergy • Find for given end points/directions
Lifting the optimal curve problem to The energy functional to minimize subject to the constraints along the curve:
Benefits and disadvantages • Advantages • Robust to noise • No erroraccumulation • Disadvantages • Computationallyexpensive • Needs more boundaryconditions • Cansacrificelocalerrorforglobaloptimization
New idea: combine local and global • Not global energy minimizers, but limit search to smaller search areas and combine solutions • Addadditionalconstraints to limit search space • Limit curvature to bebelowthreshold • Do extra constraintschangeoptimal curve problem?
Search area Simulateconvection Geodesics to endpoints
Theoreticalbenefits • Advantages • Robust to noise • Computationalintermediate • Balance between local and global error • Limits to localorglobalmethodfor search areasmallorlarge • Disadvantages • Extra parameters thatneed to betuned
How to find optimum curve? • Minimizermaynotexist • Minimizermaynotbeunique • Different options • UseDijkstra to findcheapestpathalongtree-graph (restrictsenergyfunction) • Try discrete subset of curves • Getanapproximateminimizer and iterativelyrefineit
Past and Plans Article published in NM-TMA (feb ‘13) Enhancement Article published in JIMV Refineideas and publishproof-of-concept to MICCAI conference (June) Expandforjournalarticle Visit Berlin to workonnewnon-linearenhancementtechnique (August)