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P025 MPRAGE Pre-Contrast. P025 MPRAGE w/ Z-Score < -4. Notes. This was accomplished by doing an inverse nonlinear warp from MNI to the SPGR FA 18, then to the MPRAGE space with a linear transform (ideally these transforms should be combined)

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P025 MPRAGE Pre-Contrast

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P025 mprage pre contrast

P025 MPRAGE Pre-Contrast

P025 mprage w z score 4

P025 MPRAGE w/ Z-Score < -4



  • This was accomplished by doing an inverse nonlinear warp from MNI to the SPGR FA 18, then to the MPRAGE space with a linear transform (ideally these transforms should be combined)

  • Images are larger than shown, zoom in for more detail

  • Not all lesions are found by the z-score thresholding but a significant amount are

  • Large volumes of white matter are found to be significantly demyelinated: perhaps DAWM or actually revealing the “invisible disease”?

  • This was one the patients with a larger amount of low MWF volume, EDSS 5.0 SPMS

Another look at multi channel segmentation with fsl fast

Another Look at Multi-Channel Segmentation with FSL FAST



  • Same slices as shown in the z-score slides

  • Lesions of interest circled

Spgr 3 class csf

SPGR 3 class-CSF

  • Generally good CSF segmentation

  • Does not capture most lesions

Spgr 3 class gm

SPGR 3 class-GM

  • Includes some or all of lesions

Spgr 3 class wm

SPGR 3 class-WM

  • Matches nicely with the MPRAGE scan

  • Partially includes lesions

Spgr 4 class csf

SPGR 4 class-CSF

  • Generally worse than 3 class CSF

Spgr 4 class gm

SPGR 4 class-GM

  • More conservative estimate of GM, much fewer lesions included

Spgr 4 class more gm

SPGR 4 class-More GM

  • Deep GM

  • Includes many of the lesions

Spgr 4 class wm

SPGR 4 class-WM

  • Does well at excluding most focal lesions but appears to be some partially including some

  • More conservative

Spgr flair 3 class csf


  • Grabs most lesions

  • Unfortunately mis-classifies GM too

Spgr flair 3 class gm


  • Includes many regions previously seen as WM

Spgr flair 3 class wm


  • Good exclusion of lesions identified by z-score

  • Does poorly at WM and GM segmentation, misses some WM

Spgr flair 4 class csf


  • Generally worse than 3 class CSF also

  • Chokes back mask too far

Spgr flair 4 class gm


  • Still misidentifies a lot of WM as GM

  • Catches edges of our lesions of interest

Spgr flair 4 class more gm

SPGR-FLAIR 4 class-More GM

  • Again mis-includes a lot of WM

Spgr flair 4 class wm


  • Avoids lesions but also misses a lot of regular WM since those are misidentified as GM

Spgr t2 pd 3 class csf

SPGR-T2-PD 3 class-CSF

  • Decent at outside brain CSF, though catches some WM

  • Does not get any CSF inside brain

Spgr t2 pd 3 class gm

SPGR-T2-PD 3 class-GM

  • Captures our lesions of interest

  • Gets ventricle CSF

  • Not as good as SPGR 3 class

Spgr t2 pd 3 class wm

SPGR-T2-PD 3 class-WM

  • Overly greedy WM

  • Misses focal lesions but gets GM

Spgr t2 pd 4 class csf

SPGR-T2-PD 4 class-CSF

  • Same problems as with SPGR-T2-PD CSF segmentation

Spgr t2 pd 4 class gm

SPGR-T2-PD 4 class-GM

  • GM + inner CSF

  • Catches darker lesions

  • Pretty poor, also gets WM

Spgr t2 pd 4 class more gm

SPGR-T2-PD 4 class-More GM

  • Catches some lesions but overall pretty garbagey

  • Doesn’t really correspond to a distinct tissue class

Spgr t2 pd 4 class wm

SPGR-T2-PD 4 class-WM

  • A conservative estimate

  • Circled region shows possible inclusion of GM and missing of brain stem

Best csf

Best CSF

  • SPGR 3 class (includes some lesions)

  • SPGR-FLAIR 3 class (includes all lesions)

  • SPGR-T2-PD 3 class (useful for out of brain CSF, does not include lesions)

Best wm

Best WM

  • SPGR 3 class (best anatomically)

  • SPGR 4 class (conservative)

  • SPGR-FLAIR 4 class (more lesion exclusion)

Best gm

Best GM

  • SPGR 3 class (GM+lesions)

  • SPGR 4 class (deep GM+lesions)

Best lesion

Best Lesion

  • SPGR 3 class (GM+lesions)

  • SPGR-FLAIR 3 class (CSF missing some lesions)

Coming soon

Coming Soon

  • Segmentation with a priori maps

  • Ideas about how to combine maps to produce NAWM, NAGM, and lesion only masks

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