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

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

Underlying philosophy in DTI

Si

S0


From probability to diffusivity

1r1

1r1

2r2

1r2

From probability to diffusivity

  • DTI: D(g) = D P(r) = Gaussian

~2µm

2 – 3 orders of magnitude difference

1-2mm


Application dti

DTITool, BMIA group TU/e

?

Application - DTI


Different approaches

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


Hardi

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


Reality check

Reality check…

  • Long (more complicated) acquisition scheme

  • Popular for phantom data and simulations

  • Tricky mathematical models

  • Non-intuitive visualization


Reality check1

PDF = mixture of Gaussians

Reality check…

  • Scanning time ~0.5h (and much more!)

  • Phantoms like it – people don’t like it!

  • Mathematical models:


Reality check2

SH representation of ADC

Reality check…

  • Scanning time ~0.5h (and much more!)

  • Phantoms like it – people don’t like it!

  • Mathematical models:

  • m


Reality check3

HOT representation of ADC

Reality check…

  • Scanning time ~0.5h (and much more!)

  • Phantoms like it – people don’t like it!

  • Mathematical models:


And of course visualization issues

…and of course Visualization issues

[Ozarslan, MRM 2003]

[Tuch, PhD Thesis 2002]

[Liu, MRM 2004 ]


My current work ideas struggles

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.


My current work ideas struggles1

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]


Multi fieldity in hardi

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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