[MINC-development] minccmp

[Alex ZIJDENBOS]

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On Tue, Jun 17, 2003 at 05:49:11PM +1000, Andrew Janke wrote:
> 
> I'm more after what stats within voldiff do people use? (and are preferably
> voxel-based).  An equation for these might be nice too! :)

voldiff mainly produces the kappa statistic, as well as confusion
matrix, sensitivity, specificity, etc. See attached for sample
output. Vasco describes most of these in his thesis, see

   http://www.bic.mni.mcgill.ca/~alex/docs/vasco_thesis.pdf

As for AZSM (I'll let you figure out the acronym assigned by Vasco :),
that comes from my theseis work. You can find that, and my Dec 94 TMI
paper which summarizes it, in the same place (dissertation.pdf,
zijdenbos_tmi_dec_1994.pdf).

Hope this helps,

-- Alex

=========================================================================
| Alex P. Zijdenbos, Ph.D.        |                                     |
| McConnell Brain Imaging Centre  |  Phone: [+1] 514 398-5220  (office) |
| Montreal Neurological Institute |         [+1] 514 398-1996   (dept.) |
| 3801 University St., WB-208     |    Fax: [+1] 514 398-8952  (office) |
| Montreal, Quebec, H3A 2B4       |         [+1] 708 810-3309 (private) | 
| CANADA                          | E-mail:      alex@bic.mni.mcgill.ca |
=========================================================================


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Confusion matrix for the following volumes :

Volume1 (row-left) = 00097/classify/nih_chp_00097_cls_t1_classify-clean_csf-gm-wm.mnc.gz 
Volume2 (col-top)  = 00094/classify/nih_chp_00094_cls_t1_classify-clean_csf-gm-wm.mnc.gz 

Confusion matrix of class distribution 

 class         0         1         2         3     Total

    0    2979755    203336    131910    106191   3421192
    1     174444    382482    263093     92199    912218
    2      62540    330494    852565    277640   1523239
    3      81171    191183    452313    527821   1252488

Total    3297910   1107495   1699881   1003851   7109137

Collapsed confusion matrix statistics discribing different similarity measures: 

 Class   Kappa   CKappa  AZSM    Sensit. Error   Specif. Accuracy

    0	 0.7593	 0.7857	 0.8870	 0.8710	 0.1290	 0.9137	 0.8932
    1	 0.3121	 0.2770	 0.3787	 0.4193	 0.5807	 0.8830	 0.8235
    2	 0.4213	 0.3915	 0.5290	 0.5597	 0.4403	 0.8483	 0.7865
    3	 0.3263	 0.3689	 0.4679	 0.4214	 0.5786	 0.9187	 0.8311

Total	 0.5109	 0.5109	 0.6844	 0.6671	 0.3329

Combined Kappa statistics: 

Total_Kappa=0.5109    Brain_Kappa=0.3593    Paren_Kappa=0.3756



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