Dear Mark,

Thanks for taking a look.

The zip file 'RC' has been given the ref no. 436669.

There are 36 subjects (some with more than 1 MR brain hence co16, co16b for example). 

Originally I ran the programme as a job lot using the following:

Registration:


for filename in co01 co02 co03 co04 co05 co07 co08 co09 co09b co10 co11 co11b co12 co13b co14 co14b co15 co16 co16b co17 co17b co18 co19 co20 co21 co21b co22 co23 co24 co25 co25b co25c co26 co27 co28 co29b co30 co31 co32 co32b co33 co34 co35 co36 ; do first_flirt $filename ${filename}_to_std_sub –cort ; done

 

Left Cerebellar Segmentation (I found -n 33 gave the best fit):


for filename in co01 co02 co03 co04 co05 co07 co08 co09 co09b co10 co11 co11b co12 co13b co14 co14b co15 co16 co16b co17 co17b co18 co19 co20 co21 co21b co22 co23 co24 co25 co25b co25c co26 co27 co28 co29b co30 co31 co32 co32b co33 co34 co35 co36 ; do run_first –i $filename –t ${filename}_to_std_sub.mat –n 33 –o ${filename}_L_Cereb –m ${FSLDIR}/data/first/models_336_bin/intref_puta/L_Cereb.bmv –intref ${FSLDIR}/data/first/models_336_bin/05mm/L_Cereb_05mm.bmv ; done

 

Right C Segmentation (found -n 31 gave the best fit):


for filename in co01 co02 co03 co04 co05 co07 co08 co09 co09b co10 co11 co11b co12 co13b co14 co14b co15 co16 co16b co17 co17b co18 co19 co20 co21 co21b co22 co23 co24 co25 co25b co25c co26 co27 co28 co29b co30 co31 co32 co32b co33 co34 co35 co36 ; do  run_first –i $filename –t ${filename}_to_std_sub –n 31 –o {filename}_R_Cereb –m ${FSLDIR}/data/first/models_336_bin/intref_puta/R_Cereb.bmv –intref ${FSLDIR}/data/first/models_336_bin/05mm/R_Cereb_05mm.bmv ;

done

 

Export to excel:


for filename in co01 co02 co03 co04 co05 co07 co08 co09 co09b co10 co11 co11b co12 co13b co14 co14b co15 co16 co16b co17 co17b co18 co19 co20 co21 co21b co22 co23 co24 co25 co25b co25c co26 co27 co28 co29b co30 co31 co32 co32b co33 co34 co35 co36 ; do LCereb=`fslstats ${filename}_L_Cereb -v | awk '{print $2}'`; RCereb=`fslstats ${filename}_R_Cereb -v | awk '{print $2}'`; echo "${filename},${LCereb},${RCereb}" >> Cerebellum1.csv ; done

 

The last command gave huge values for the cerebellum, some twice as big as expected. I then ran the command adding intensity values instead (in bold below) which gave more realistic volumes but still too small (which I think is due to the original segmentation missing some peripheral cerebellar tissue):


for filename in co01 co02 co03 co04 co05 co07 co08 co09 co09b co10 co11 co11b co12 co13b co14 co14b co15 co16 co16b co17 co17b co18 co19 co20 co21 co21b co22 co23 co24 co25 co25b co25c co26 co27 co28 co29b co30 co31 co32 co32b co33 co34 co35 co36 ; do LCereb=`fslstats ${filename}_L_Cereb -l 6.5 -u 7.5 -v | awk '{print $2}'`; RCereb=`fslstats ${filename}_R_Cereb -l 46.5 -u 47.5 -v | awk '{print $2}'`; echo "${filename},${LCereb},${RCereb}" >> Cerebellum1.csv ; done


Thanks again for taking a look.


Best Wishes


Stuart

 


On 12 July 2011 17:38, Mark Jenkinson <[log in to unmask]> wrote:
Dear Stuart,

This looks correct.
Possibly it is something unusual with your data or some
difference with the manual outlining protocol used by the
CMA to train with versus what you'd prefer to see.

I can't tell without seeing the data, so can you please upload
it to:
  http://www.fmrib.ox.ac.uk/cgi-bin/upload.cgi
and send me the reference number.

All the best,
       Mark


On 12 Jul 2011, at 17:33, Stuart Currie wrote:

> Hi Mark,
>
> Thanks for replying.
>
> Using first_flirt and after initial registration:
>
> First_flirt input image subject1_to_std_sub_cort
>
>
> I'm trying to calculate cerebellar volume by calculating right and left hemispheres:
>
> e.g. for the left hemisphere:
>
> run_first -i file name -t subject1_to_std_sub.mat -n 33 -o cerebellum -m ${FSLDIR}/data/first/models_336_bin/intref_puta/L_Cereb.bmv -intref ${FSLDIR}/data/first/models_336_bin/05mm/L_Puta_05mm.bmv
>
>
>
> when I view this over the original nii.gz images on fslview it is clear that the cerebellar model is missing some of the peripheral tissue.
>
>
>
> I have tried changing the -n (number of modes of variation) up and down from 33 but 33 seems to be the best fit. Similarly 31 seems to work best for the right hemisphere. Unfortunately when I finally receive the volume data the total cerebellar volumes are ~ 50 cm3, no where near the ~ 110 cm3 expected.
>
>
>
> Is there a way of modifying the cerebellar model further to gain a better fit?
>
>
>
> Cheers
>
>
>
> Stuart
>
>
> On 12 July 2011 16:57, Mark Jenkinson <[log in to unmask]> wrote:
> Can you be a bit more specific?
> All the best,
>        Mark
>
> On 12 Jul 2011, at 16:39, Stuart Currie wrote:
>
> > Trying to run the cerebellar volume command but seems to be underestimating volumes despite changing the -n value to attempt best fit. Any suggestions?
> >
>
>
>
> --
>
> Dr Stuart Currie
> BSc, MB ChB, MRCS, FRCR
> Clinical Research Fellow/Honorary Neuroradiology Fellow
> Academic Unit of Radiology
> University of Sheffield
> C Floor
> Royal Hallamshire Hospital
> Sheffield
> S10 2JF
>



--
 
Dr Stuart Currie
BSc, MB ChB, MRCS, FRCR
Clinical Research Fellow/Honorary Neuroradiology Fellow
Academic Unit of Radiology
University of Sheffield
C Floor
Royal Hallamshire Hospital
Sheffield
S10 2JF