SIENAX Report sienax structural -d -r

BET brain extraction results

FLIRT standard space registration results

Field-of-view and standard space masking
Red shows the standard-space-based brain mask combined with the field-of-view mask (if used). Blue shows the original BET-derived brain mask. Green shows the intersection of the two.

Final SIENAX segmentation results

Whole-brain segmentation

Peripheral cortex masked segmentation

Ventricle masked segmentation

Estimated volumes:

tissue             volume    unnormalised-volume
pgrey              680122.38 570022.69 (peripheral grey)
vcsf               42537.67 35651.58 (ventricular CSF)
GREY               849052.00 711605.61
WHITE              682364.36 571901.73
BRAIN              1531416.36 1283507.34

SIENAX Methods

Brain tissue volume, normalised for subject head size, was estimated with SIENAX [Smith 2001, Smith 2002], part of FSL [Smith 2004]. SIENAX starts by extracting brain and skull images from the single whole-head input data [Smith 2002b]. The brain image is then affine-registered to MNI152 space [Jenkinson 2001, Jenkinson 2002] (using the skull image to determine the registration scaling); this is primarily in order to obtain the volumetric scaling factor, to be used as a normalisation for head size. Next, tissue-type segmentation with partial volume estimation is carried out [Zhang 2001] in order to calculate total volume of brain tissue (including separate estimates of volumes of grey matter, white matter, peripheral grey matter and ventricular CSF).

[Smith 2001] S.M. Smith, N. De Stefano, M. Jenkinson, and P.M. Matthews.
   Normalised accurate measurement of longitudinal brain change.
   Journal of Computer Assisted Tomography, 25(3):466-475, May/June 2001.

[Smith 2002] S.M. Smith, Y. Zhang, M. Jenkinson, J. Chen, P.M. Matthews, A. Federico, and N. De Stefano.
   Accurate, robust and automated longitudinal and cross-sectional brain change analysis.
   NeuroImage, 17(1):479-489, 2002.

[Smith 2004] S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady, and P.M. Matthews.
   Advances in functional and structural MR image analysis and implementation as FSL.
   NeuroImage, 23(S1):208-219, 2004.

[Smith 2002b] S.M. Smith.
   Fast robust automated brain extraction.
   Human Brain Mapping, 17(3):143-155, November 2002.

[Jenkinson 2001] M. Jenkinson and S.M. Smith.
   A global optimisation method for robust affine registration of brain images.
   Medical Image Analysis, 5(2):143-156, June 2001.

[Jenkinson 2002] M. Jenkinson, P.R. Bannister, J.M. Brady, and S.M. Smith.
   Improved optimisation for the robust and accurate linear registration and motion correction of brain images.
   NeuroImage, 17(2):825-841, 2002.

[Zhang 2001] Y. Zhang, M. Brady, and S. Smith.
   Segmentation of brain MR images through a hidden Markov random field model and the expectation maximization algorithm.
   IEEE Trans. on Medical Imaging, 20(1):45-57, 2001.