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High Angular Diffusion Imaging and its Visualization…

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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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