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# High Angular Diffusion Imaging and its Visualization… - PowerPoint PPT Presentation

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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Presentation Transcript

• Limitations of DTI

• Why HARDI is better?!?

• Different HARDI models

• My ideas and current work

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

• What if…

• Measure > 6(20) gradient directions

• Give more time to the molecules to do their job

• What if…

• Use high b-values: <2000s/mm2 (w.r.t gradient strength and effective time)

= 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

• Long (more complicated) acquisition scheme

• Popular for phantom data and simulations

• Tricky mathematical models

• Non-intuitive visualization

Reality check…

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

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

• Mathematical models:

Reality check…

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

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

• Mathematical models:

• m

Reality check…

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

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

• Mathematical models:

…and of course Visualization issues

[Ozarslan, MRM 2003]

[Tuch, PhD Thesis 2002]

[Liu, MRM 2004 ]

• 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.

• 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]

• 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