For each vertex, the label code. However, the design of this file format undermines both of those expectations. Each "row" stores a vertex number, which would seem redundant, but because it is present could potentially result in an annotation file listing the vertices out-of-order, and particular vertices more than once or not at all.
I'm not sure that ever happens; reassuringly, the code for MRISwriteAnnotation stores every vertex exactly once and in order of vertex-number. However, MRISreadAnnotation does pay attention to vertex-number, and thus, without complaining, could load annotations with vertices out of order or duplicated. This bit integer is stored in the file in Big-endian order as with all the int4 values , so the actual order of the colors in the file is ABGR.
The fact that the "ColorLUT" is called a "Color Lookup Table" in the first place asserts the idea that the label code is used to look up the color. With the annotation file, the reverse is needed: the color has to be used to look up the label code. This has several awkward consequences: Every region that you wish to distinguish must have not only a unique label code but also a unique color.
It may be wise to maintain a single master ColorLUT file and enforce some discipline about how you choose label codes and colors to ensure no duplicates. I think. It is conceivable to have an annotation file with vertices "colored" with annotation values that don't correspond to any label. Additionally, this confusion between the annotation of a vertex versus the label of a vertex extends to tksurfer. There, it is possible to recolor a region's vertices to match the vertices of another region.
At that point, though the colors match, the vertices in the two regions retain their different labels. However, if this state of annotation is saved to a file, the per-vertex data saves the annotation values ie: colors only , and thus no longer distinguishes the two regions, which can be seen when the annotation file is reloaded into tksurfer. Related terminology issues The vocabulary in this area of FreeSurfer has not been tightly controlled, leading to confusion as to what different words actually refer to the same things, and instances where the same word refers to different things.
A surface parcellation eg: aparc is captured by attaching labels to vertices, and storing the result in either a set of label files, or more likely an annotation file. The freesurferformats also comes with GIFTI write support, including a general data array writer as well as custom writers for the previously listed kinds of neuroimaging data.
The wrapper functions in freesurferformats support extraction of the data for a specific brain model surface mesh , and map the data to the appropriate vertex indices of the surface based on the CIFTI metadata. This software is for research puposes only and shall not be used for any clinical use.
The package is on CRAN , so you can simply:. The package is also available from neuroconductor. Just install the missing system dependencies and retry. Note: You can ignore this section unless you want to build the freesurferformats package from the source code. A system dependency is a non-R software that is needed for the installation of a package. System dependencies cannot be installed automatically using the R package system, so you need to install them manually or using the package manager of your operating system.
If you do not have it installed already, before installing freesurferformats , run the following command in your system shell not in R :. The documentation can be accessed from within an R session after you have loaded the freesurferformats package:.
One of the example subjects that comes with FreeSurfer is bert. If you have FreeSurfer installed, you can start GNU R by typing R in your favourite terminal application and run the following commands:. The freesurferformats package is free software , published under the MIT license. A paper is in the making. For now, please cite the R package. You can generate the citation for the version you use by typing the following command in R:.
This will ouput something like this but for the version you actually used, which is important for reproducibility :. Note that this DOI always points to the latest version, so be sure to still include the package version in the citation. You can install the latest development version directly from Github if you need features which have not been released yet. While the development versions may have new features, you should not consider their API stable. Wait for the next release if you are not fine with adapting your code to API changes later.
If in doubt, do not use the dev version. This package comes with lots of unit tests. To run them, in a clean R session:. Travis CI under Linux. AppVeyor CI under Windows. Test coverage. The displayed status represents the development version.
If you found a bug, have any question, suggestion or comment on freesurferformats, please open an issue. I will definitely answer and try to help. The label is visible in coronal slice To jump to that slice, double click on the coordinates [,,] next to where it says 'orig' in the Cursor window pane. The last number is the slice number. Change it to and hit enter. To view the label on the surface, first load the the subject's inflated surface in freeview in another terminal window using the command below.
At the top menu bar, select the 3D view. Next to 'Label', select 'Load'. In the window that pops up, navigate to the label directory if it is not already in it and select lh. Hit 'OK'. The label loaded on the inflated surface will look like this: Note : If you want to use a pre-existing label and register it to fsaverage, be aware that this might involve two instances of resampling and the results might not be as accurate as they would be if you drew the label on fsaverage.
Please contact the FreeSurfer team to get more details on this process if you have any concerns. Just like in TkSurfer if you have used it before.
Individual Stats files During the FreeSurfer processing stream, via the recon-all script, some statistical output files are generated.
These tables include information on each labeled region for the individual subject. You can view these output files via the terminal or a text editor. For example, you can obtain information such as the volume of left hippocampus and its mean intensity from this file.
Following this there is information about the volume of the entire brain. The next section of this file defines the column headers, field name, and units for the rest of the table. The remainder of the table shows this information for all the structures that are labeled in the aseg.
Remember, press 'q' if you want to quit the 'less' command. For example, you can obtain information such as, how big is left superior temporal gyrus and its average thickness from this file. The measures at the top show the number of vertices in the cortex NumVert and the surface area of the cortex SurfArea.
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