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High Angular Diffusion Imaging and its Visualization…

High Angular Diffusion Imaging and its Visualization…. Limitations of DTI Why HARDI is better?!? Different HARDI models My ideas and current work. Underlying philosophy in DTI. S i. S 0.  1 r 1.  1 r 1.  2 r 2.  1 r 2. From probability to diffusivity.

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High Angular Diffusion Imaging and its Visualization…

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  1. High Angular Diffusion Imaging and its Visualization… • Limitations of DTI • Why HARDI is better?!? • Different HARDI models • My ideas and current work

  2. Underlying philosophy in DTI Si S0

  3. 1r1 1r1 2r2 1r2 From probability to diffusivity • DTI: D(g) = D P(r) = Gaussian ~2µm 2 – 3 orders of magnitude difference 1-2mm

  4. DTITool, BMIA group TU/e ? Application - DTI

  5. Different approaches • What if… • Measure > 6(20) gradient directions • Give more time to the molecules to do their job • What if… • Measure: 200-300 gradient directions • Use high b-values: <2000s/mm2 (w.r.t gradient strength and effective time) = HARDI

  6. HARDI • Many different approaches • DSI , q-ball • High-order tensor models w.r.t. ADC • SH representation • PAS-MRI • Multi-compartment models etc.. • All in common: avoid Gaussian model fitting

  7. Reality check… • Long (more complicated) acquisition scheme • Popular for phantom data and simulations • Tricky mathematical models • Non-intuitive visualization

  8. PDF = mixture of Gaussians Reality check… • Scanning time ~0.5h (and much more!) • Phantoms like it – people don’t like it! • Mathematical models:

  9. SH representation of ADC Reality check… • Scanning time ~0.5h (and much more!) • Phantoms like it – people don’t like it! • Mathematical models: • m

  10. HOT representation of ADC Reality check… • Scanning time ~0.5h (and much more!) • Phantoms like it – people don’t like it! • Mathematical models:

  11. …and of course Visualization issues [Ozarslan, MRM 2003] [Tuch, PhD Thesis 2002] [Liu, MRM 2004 ]

  12. My current work, ideas, struggles… • Comparing most promising methods (w.r.t. feasibility on vivo data) and improve it • DOT and q-ball • Answer the mysterious 42 question: “How high should be the “high” b-value?” • DTI is not dead! Combining with HARDI. Define measure where 2nd order tensor is sufficient! • Segmentation on HARDI data.

  13. My current work, ideas, struggles… • More intuitive HARDI visualization => doctors don’t like glyphs • Fiber tracking on HARDI • Combining different modalities • Use of fMRI activation zones as seeding regions for white matter tractography [INRIA-McGill] [Hardenbergh, IEEE Vis 2005]

  14. Multi-fieldity in HARDI • Multiple measurements over same domain • High-dimensional data • High-order mathematical models (HOT and SH) • Combining HARDI+fMRI =>Jorik • Sufficient order w.r.t. encapsulated information => Stef

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