FLIRT/UserGuide - FslWiki
So what you should do is: flirt -in T1 -ref FA -omat pdl-inc.info then: flirt -in T1 Kristen, Ann > Objet: Re: [FSL] T1 and DTI Registration. Subject: Re: Flirt-- coregistration between T1 and DTI B0 image. From: Reply- To: FSL - FMRIB's Software Library. Date. FSL is a comprehensive library of analysis tools for FMRI, MRI and DTI brain " FLIRT: linear registration"; the functional-oriented functions invole "SUSAN noise .
However, registration of such data is more challenging than for three-dimensional scalar images, not only because of its high dimensionality hundreds of volumes or noise and artifacts present in MR scans Jones et al. The simplest approach to DW-MRI registration consists in registering these datasets using a single transformation obtained from a representative volume, such as the Fractional Anisotropy FA Pierpaoli and Basser,or the non-diffusion-weighted b0 image.
However, DW-MR registration using a single volume can be unsatisfactory, since it disregards the fiber orientation information provided by the diffusion-weighted volumes. Besides the spatial registration of DTI data, the images must also be reoriented so as to be consistent with the transformations made to the anatomy Alexander et al.
In order to overcome known limitations of the diffusion tensor model Skare et al. Nevertheless, relying on such diffusion models might not completely capture the information contained in the raw data and could therefore affect the registration accuracy.
In addition, these models are not generic and rely on specific assumptions.
The spatial registration with an angular interpolation correction of the image intensities attempts to match the registration of the underlying fiber structures. The evaluation of AI was entirely qualitative in Tao and Miller In this work, we extend the AI algorithm to non-linear registration and perform a wide range of tests that include human brain DW-MRIs undergoing known synthetic linear and non-linear transformations. Our implementation also handles the registration of DW-MRI datasets obtained with different gradient tables.
A recent work Wang et al. Some other works have been recently published addressing the issue of gradient reorientation of DW-MRIs, in the context of image registration Dhollander et al.
In particular, Yap et al. In fact, Dhollander et al. This is a well-known problem in DTI registration Alexander et al. In order to account for the complex rotation effect that shearing, stretching, or non-uniform scaling can have on the fiber orientation, Alexander et al. However, as Zhang et al. Furthermore, some areas can be given extra weighting such as the ventricles so that the registration is most accurate near these structures, but still uses information from the rest of the image e.
A description of the available GUI interfaces is also available. For each of the programs described here, a usage message which describes the full list of available options can be obtained by running the program with no options. See also the list of common example usages. The main options are: For these usages the reference volume must still be specified as this sets the voxel and image dimensions of the resulting volume.
Cost Function Weighting Weighting volumes can be specified using -refweight, -inweight or both. Note that this is different from masking the original images, as masking introduces artificial boundaries whereas weighting does not.
Note that it does not perform any search in 2D mode, and cannot deal with 2D to 3D registrations. Interpolation Methods This includes Nearest Neighbour, a family of Sinc-based methods three window types - rectangular, Hanning and Blackman with configurable window width, and spline a highly efficient method, with similar output characteristics to sinc. The interpolation is only used for the final transformation and in applyxfmnot in the registration calculations.
In addition, there is the BBR cost function which utilises a segmentation of the reference image to define a boundary, and it is the intensity differences in the input image, across the transformed boundary, that contribute to the cost. The pre-requisites to use this method are: This script will either use an existing white-matter segmentation of the structural image, or create one itself, to define a white-matter boundary.
We recommend that the structural image is bias-corrected separately beforehand if there is obvious bias field present. The script is also capable of using fieldmaps to perform simultaneous registration and EPI distortion-correction.
The inputs echospacing and pedir both refer to the EPI image not the fieldmap and are the same as required for FEATbut be careful to use the correct units.
It can read and write ascii 4x4 matrices.
In addition, it can be used to concatenate two transforms using -concat with the second transform or to find the inverse transformation using -inverse.
If the option -mm is used then both input and output coordinates will be in mm coordinates, otherwise with -vox both coordinates will be in voxel coordinates. For conversion between voxel and mm coordinates it is necessary to use either img2stdcoord or std2imgcoord see below.
Note that the source coordinates can either be input via a file or via a pipe and for the latter the "-" symbol is used as the filename. The format in either case is three numbers per line, space separated. The difference between an exclusion and a termination mask is that in the latter case, the tract is stopped at the target mask, but included in the calculation of the connectivity distribution, while in the former case, the tract is completely discarded.
Neuroimaging Data Processing/FSL
This option is only active when the seed mask is a single mask. In the example on the right, seed voxels in the thalamus are classified according to the probability of connection to different cortical target masks. Use the add button to locate each target mask.
Targets must be in the same space as the seed mask. When all targets are loaded you can press the save list button to save the list of targets as a text file.
If you already have a text file list of required targets including their path then you can load it with the load list button. In these output images, the value of each voxel within the seed mask is the number of samples seeded from that voxel reaching the relevant target mask.
The value of all voxels outside the seed mask will be zero. There are command line utilities that can be run on these outputs: Number of samples default This determines the number of individual pathways or samples that are drawn through the probability distributions on principle fibre direction see appendix for more details on the modelling and tractography methods. By default this is set to as we are confident that convergence is reached with this number of samples.
However, reducing this number will speed up processing and can be useful for preliminary or exploratory analyses. Curvature Threshold default 0. We limit how sharply pathways can turn in order to exclude implausible pathways. This number is the cosine of the minimum allowable angle between two steps. By default this is set to 0.
Adjusting this number can enable pathways with sharper angles to be detected. If this option is selected then FDT prints additional logging information to screen while it is running. By default, we terminate pathways that loop back on themselves -i. Use modified Euler streamlining: Use modified Euler integration as opposed to simple Euler for computing probabilistic streamlines.
More accurate but slower. Maximum number of steps default By default, samples are terminated when they have travelled steps. Using a step length of 0. These values can be adjusted if required.
FLIRT/StepByStep - FslWiki
Step length default 0. This determines the length of each step. This setting may be adjusted from default e. Use anisotropy to constrain tracking: The tracts stop if the anisotropy is lower than a random variable between 0 low anisotropy and 1 high anisotropy. This option corrects for the fact that connectivity distribution drops with distance from the seed mask. If this option is checked, the connectivity distribution is the expected length of the pathways that cross each voxel times the number of samples that cross it.
Threshold on the volume fraction of subsidiary fibres. Discard streamlines that stop before reaching a length in mm bigger than this threshold.
The default is to accept all lengths. When tracking from a volume-type seed, tracking is by default run from the centre of the voxels. Use this option to jitter the starting point in a sphere of given radius in mm.
Output lenght of the pathways --pd: Writes the sum of the lenghts from all the accepted streamlines.
This affects all the distribution maps and all the connectivity matrices genereted. Output mean path lenghts --ompl: Writes the mean of the lengths from all the accepted streamlines. Waypoint options only used if waypoint masks are set in the main tab: Apply waypoint independently in both directions: Streamlines are run in both directions from the starting point. By default, the two halves are considered independently for the waypoint inclusion criterion. Untick this box if you want them to be considered together as one streamline.
Force waypoint crossing in the listed order: