The alignment process uses two alignment methods: (1) the mrvista function, rxalign, for a rough alignment, and then (2) KNK's alignment for

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Lee Hancock
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1 Alignment (Allegra) Download example alignment script here. Anatomical images are collected at much higher resolution (isotropic 1 mm voxels) than functional images (isotropic 2 mm voxels; sometimes 2.5). The contrast between white and gray matter in anatomical scans (T1-weighted) is also higher than in functional (T2*-weighted) images. For this reason, the functional data is registered to a low-resolution T1- or T2-weighted inplane scan, which in turn is used to align the functional images with the higher-resolution, whole-brain anatomical images. The alignment process uses two alignment methods: (1) the mrvista function, rxalign, for a rough alignment, and then (2) KNK's alignment for fine-tuning. The process is mostly automated via script ( s_aligninplanetoanatomical.m), but requires user input at multiple stages, and takes anywhere from a few minutes to a few hours. Required repositories are vistasoft and knkutils. Overview of alignment process Using rxalign GUI Open GUI Find decent alignment Using KNK alignment code Modify rxalign transformation matrix to KNK format (4a) Pre-condition the volumes (4b) Open alignment GUI (4c) Define ellipse covering brain matter (4d) Automatic alignment (coarse) (4e) Automatic alignment (fine) (4f) Optional: Automatic alignment (affine transformation) (5) Export and save transformation in mrvista format (6) Check alignment Overview of alignment process From JW documentation of alignment script: Use rxalign to roughly align inplane and high-resolution anatomy Export best alignment (4x4 transformation matrix describing a rigid transformation) Use exported xform matrix as starting point for KNK's alignment code In KNK alignment code: a. b. c. d. e. Pretreat volumes (contrast/luminance normalization) Fit an ellipse that covers the brain, but not the skull. This ellipse determines which voxels to use during the alignment process. The point is to avoid artifacts like fat, which move around a lot and can confuse the alignment Do coast alignment using mutual information metric Do fine alignment using informational metric (Optional) Do full affine transformation in order to compensate for scaling issues due to nonlinearities/miscalibration of the transform matrix. 5. Save xform matrix as new mrvista alignment Using rxalign GUI We use the rxalign GUI to get a decent alignment manually. This alignment will be used as a starting point for KNK's alignment code, so it doesn't have to be very good just somewhere in the ballpark of being right. Once you are finished, select "store" to save your alignment for backtracking. Open GUI In Matlab command window, navigate to the session directory. Then type rxalign to open the GUI. cd Volumes/server/Project/project_name/session_id rxalign Find decent alignment Extensive instructions and tips on using rxalign can be found on the Vista Lab Wiki. Generally speaking, in the rxalign GUI, you attempt to make

the prescribed slice (the interpolated slice, middle figure in image below) look as close as possible to the reference slice (right figure below) using the Rx figure (left figure) as a guide for

2 the prescribed slice (the interpolated slice, middle figure in image below) look as close as possible to the reference slice (right figure below) using the Rx figure (left figure) as a guide for determining the slice prescription. Note that this is a rigid-body transformation, controlled by the sliders in the top figure in the image below. The instructions on the Vista Lab Wiki are old and are oriented towards researchers who are using rxalign to set the final alignment (a frustrating process). As a first pass, adjust the slice prescription in the far left window by double clicking in the back of the brain. Use the "Translate Ant-Pos" slider in the upper right window to adjust position, and then "Rotate Axials CW" slider in upper middle window to adjust angle. The slices should extend slightly beyond the back of the brain and be fairly oblique (about perpendicular to the calcarine). Now scroll to back of the brain in prescription volume and adjust slice prescription so there is same "amount" of brain in the interpolate and reference slices. If necessary, look for another major landmark to compare the two slices. A useful way to check if the alignment is roughly correct is to open a comparison window (window --> Open Rx/Ref Comparison Window). This allows for toggling between the interpolated slice and the reference slice and better judge the overlap. Keep in mind that we are merely using the rxalign results as a starting point for an automated alignment procedure, so it only needs to in broad ballpark range.

Using KNK alignment code Functions for automatically find coarse and fine alignment. A script containing the following commands can be copied from another session (s_aligninplanetoanatomical).

3 Using KNK alignment code Functions for automatically find coarse and fine alignment. A script containing the following commands can be copied from another session (s_aligninplanetoanatomical). It should run as is. Alternately, use the information below to write your own script. Modify rxalign transformation matrix to KNK format rxalignment = rx.xform; rxalignment([1 2],:) = rxalignment([2 1],:); rxalignment(:,[1 2]) = rxalignment(:,[2 1]); knk.torig = rxalignment; knk.trorig = matrixtotransformation(knk.torig,0,rx.volvoxelsize,size(rx.ref),size(rx.ref).* rx.refvoxelsize); (4a) Pre-condition the volumes JW note: although it's sensible to do this, not sure how much of difference this makes % Pre-condition volpre = preconditionvolume(rx.vol,[],[],[99 1/3]); refpre = preconditionvolume(rx.ref); close all (4b) Open alignment GUI Open the KNK alignment GUI, which consists of three windows: (1) upper left, target, which is the low-resolution image being aligned, (2) bottom

4 left, reference, which is the high-resolution image being aligned to, and (3) top right, overlay, which is the target and reference overlaid. By selecting this image and hitting <'>, you can toggle between the reference and target images. This is useful to do after each alignment check to make sure nothing crazy has happened and that alignment is generally improving. Be careful not to hit any other keys, as this will manually adjust the alignment. % open knk alignment GUI alignvolumedata(volpre,rx.volvoxelsize,refpre,rx.refvoxelsize,knk.trorig); (4c) Define ellipse covering brain matter Using the KNK GUI, define an ellipse that covers the brain, and ONLY the brain. This ellipse defines the voxels actually used during the alignment, so do not want to include fat or skull. %% 4b Define ellipse [~,mn,sd] = defineellipse3d(refpre); Help for defining the 3D ellipse in the GUI can be found in the documentation for defineellipse3d. Broadly speaking, use ws/ad/qe to adjust position of the ellipse and ik/jl/uo to change size of the ellipse. Check all slices to ensure the 3D ellipse ONLY contains brain matter. Err on the small side if in question; the ellipse does not need to perfectly fill the brain (which is impossible anyway since the brain isn't an ellipse). An example of a reasonable ellipse is below. (4d) Automatic alignment (coarse) Computes coarse, rigid-body alignment. After each step, toggles overlay window back and forth. Watch this window to check that alignment is generally improving. This step is pretty fast, taking 30 seconds to a few minutes, depending on how good your rxalign alignment is.

5 usemi = false; alignvolumedata_auto(mn,sd,0,[4 4 2],[],[],[],useMI); % rigid body, coarse, mutual information metric (4e) Automatic alignment (fine) Performs fine rigid-body transformation using mutual information metric. This step takes a few minutes. alignvolumedata_auto(mn,sd,0,[1 1 1],[],[],[],useMI); (4f) Optional: Automatic alignment (affine transformation) The alignment following the fine, rigid-body transform is generally very good toggle (apostrophe key) between overlay and target images in GUI window to check. An affine transformation can improve alignment, but it also can lead to significant distortion of the brain if it gets stuck in some local minima. We recommend skipping to steps 5 and 6 and saving the rigid-body only alignment before coming back to affine transformation. After the affine transform, inspect the overlay window. If it looks crazy, discard it. If it looks good, then proceed to steps 5 and 6 and overwrite the rigid-body only alignment. This step takes a few minutes. alignvolumedata_auto(mn,sd,[ ],[2 2 1],[],[],[],useMI,1e-3); alignvolumedata_auto(mn,sd,0,[2 2 1],[],[],[],useMI,1e-3); alignvolumedata_auto(mn,sd,[ ],[2 2 1],[],[],[],useMI,1e-3); alignvolumedata_auto(mn,sd,0,[2 2 1],[],[],[],useMI,1e-3); alignvolumedata_auto(mn,sd,0,[1 1 1],[],[],[],useMI,1e-3); alignvolumedata_auto(mn,sd,0,[1 1 1],[],[],[],useMI,1e-3); alignvolumedata_auto(mn,sd,0,[1 1 1],[],[],[],useMI,1e-3); (5) Export and save transformation in mrvista format Check the alignment by toggling ( ' key) between reference and interpolated slices in the window opened by the auto-alignment procedure. You should notice little to no movement of the brain, though the skull itself might become deformed. If satisfied, save and export the alignment. % Export the final transformation tr = alignvolumedata_exporttransformation; % make the transformation into a 4x4 matrix (mrvista format) T = transformationtomatrix(tr,0,rx.volvoxelsize); % Save as alignment for your vista session vw = inithiddeninplane; mrglobals; mrsession.alignment = T; savesession; (6) Check alignment Save two images showing the alignment: inplane.png and reslicedt1.png.

6 t1match = extractslices(volpre,rx.volvoxelsize,refpre,rx.refvoxelsize,tr); % inspect the results if ~exist('images', 'dir'), mkdir('images'); end imwrite(uint8(255*makeimagestack(refpre,1)),'images/inplane.png'); imwrite(uint8(255*makeimagestack(t1match,1)),'images/reslicedt1.png'); Open images in Preview and toggle between them to check alignment. Look at distinct brain features and brain edges, and try to ignore changes in contrast and in skull/fat shape. Below is an example inplane.png (left) and reslicedt1.png from an affine transformation. Toggling between these images shows a good alignment.

This exercise uses one anatomical data set (ANAT1) and two functional data sets (FUNC1 and FUNC2).

This exercise uses one anatomical data set (ANAT1) and two functional data sets (FUNC1 and FUNC2). Exploring Brain Anatomy This week s exercises will let you explore the anatomical organization of the brain to learn some of its basic properties, as well as the location of different structures. The human