1 / 33

Statistical Parametric Mapping

Statistical Parametric Mapping. Lecture 11 - Chapter 13 Head motion and correction. Textbook : Functional MRI an introduction to methods , Peter Jezzard, Paul Matthews, and Stephen Smith. Many thanks to those that share their MRI slides online. http://www.fmrib.ox.ac.uk/fsl/.

ormand
Download Presentation

Statistical Parametric Mapping

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Statistical Parametric Mapping Lecture 11 - Chapter 13 Head motion and correction Textbook: Functional MRI an introduction to methods, Peter Jezzard, Paul Matthews, and Stephen Smith Many thanks to those that share their MRI slides online

  2. http://www.fmrib.ox.ac.uk/fsl/

  3. Head motion correction by MCFLIRT • FSL software for Motion Correction using FMRIB’s Linear Image Registration Tool - FLIRT.

  4. 1 2 3 4

  5. 4x4 Affine transform matrix used with 3-D images m14, m24, and m34 are x, y, and z translations 3 each rotations, scales, shears Let R represent (x, y, z) column vectors and M the 4x4 transform matrix R’ = M R when you want to calculate primed location from unprimed one R = M-1 R’ when you want to calculate unprimed location from primed one

  6. 4x4 translation matrix T (3 parameters) M= [S][Rx][Ry][Rz][T] 4x4 scale matrix S (3 parameters) rotation matrix Rx for rotation about x-axis (1 parameter) rotation matrix Ry for rotation about y-axis (1 parameter) rotation matrix Rz for rotation about z-axis (1 parameter) Order of matrices important. Above ordering does translations first to match origins, then rotations about new origin, and finally scaling of the aligned image. For MC of fMRI no scale, i.e. use on 3 translation and 3 rotation parameters.

  7. 1 2 3 4

  8. Nearest neighbor leads to similar image histograms in transformed images but least accurate in terms of interpolation values. Sinc interpolation is considered to be the most accurate. Trilinear is intermediate in quality but relative fast. Mango provides these three interpolation options when saving an image with transform applied.

  9. 1 2 3 4

  10. Same Modality Motion Correction

  11. 1 2 3 4

  12. 1 2 3

  13. Talariach's Coordinate System Z = +1 mm • AC-PC line • AC as origin • Bounding Box • 136 x 172 x 118 mm • Right-handed system Origin (AC)

  14. Averages of Anatomy & Function Average MRI - 16 Subjects ( 3-D Gradient Echo ) Average PET - 15 Subjects ( FDG )

  15. CC TN SC CB Fitted AC-PC Line Manual SN with High-Resolution MRI Mango has a plugin for fitting high resolution MRI to the Talairach standard.

  16. CT PET MRI SPECT Multi-modality registration to a standard brain space (i.e. a particular brain atlas).

  17. Using FLIRT to fit a T1W MR image to the MNI305 3-D average brain template (template brain feature outline indicated by red lines). Note the large rotation about the y-axis indicated in the left image.

  18. Atlas Based Registration of fMRI EPI structural MNI152 M1 M2 M= [M2][M1] MNI152 structural brain template is average of 152 3-D T1W images after affine registration. What is a 7 DOF transform? All three scales are identical to correct for possible differences in spatial calibrations.

  19. Global (affine) vs. Regional (warping) to target brain 4x4 affine transform registration to target brain High degree of freedom warp to register to target brain (~2x105 deformation vectors) Target Brain This could be stage 2 in fMRI alignment to atlas.

  20. 1 2 3 4

  21. 1 2 R’ = MR For 6 DOFs M includes rotations about x, y, and z axes and translations along x, y, and z. Total motion is calculated from distance = {(x’-x)2+ (y’-y)2 +(z’-z)2}1/2 calculated for each voxel within the brain.

  22. Figure 13.1. Motion correction in a finger tapping experiment. Fig 1a (upper figure) shows the motion component ( z translation) exhibiting the strongest stimulus-correlated motion. The experimental “on” periods are shown at the bottom of the figure. Fig 1b (lower figure) shows a set of superior axial images with no correction (top row), after realignment only (middle row) and following full correction( bottom row). Full correction models signal loss due to movement.

  23. Figure 13.2. Motion correction in a visual stimulation experiment. Fig 2a (upper figure) shows the motion component ( z translation) exhibiting the strongest stimulus-correlated motion. The experimental “on” periods are shown at the bottom. Fig 2b (lower figure) shows a set of superior axial images with no correction (top row), after realignment only (middle row) and following full correction( bottom row)

  24. Figure 13.3. Two slices from a group activation map ( n=6) in schizophrenic patients before ( upper row) and after (lower row) group correction for subject motion.

  25. visual No MC auditory visual MC auditory

  26. http://www.fmrib.ox.ac.uk/fsl/

More Related