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【TrackVis 教程】基于DTI的纤维追踪及显示

ChillRay 发表于 2020/12/29 23:29:47 2020/12/29

【摘要】【Update by 张常乐-06/23/2017】加入了完全版的教程信息 Diffusion Toolkit教程 NOTE: For regular users who would always use the GUI front-end, you do not have to understand th...

   【Update by 张常乐-06/23/2017】加入了完全版的教程信息 
 

Diffusion Toolkit教程

NOTE: For regular users who would always use the GUI front-end, you do not have to understand the details of the following workflow. But having an idea of the process is recommended.

To understand how Diffusion Toolkit's GUI works, it would be necessary to know the actually workflow behind the scene. The workflow of Diffusion Toolkit (DTK) contains 4 major steps (some of them are optional).

1. Convert the raw DICOM images into a series of ANALYZE images. The command-line program to do that is diff_unpack. If the raw images are not DICOM, you will have to convert them to ANALYZE manually following the rules below:

Each analyze image must contain only one timepoint (or volume, as we often refer to. or one gradient direction, in the case of diffusion imaging).
Filenames of the images must be named with a prefix followed by number, such as xxxxx001.img, xxxxx002.img ...
Low B (B0) images must be on top. For example, if you have 60 diffusion-weighted images with 5 b0 images, you image filenames should be like this: xxxxx001 to xxxxx005 are b0 images, xxxxx006 to xxxxx65 are high b images.

2. Reconstruct the raw images.

For DTI, dti_recon does the job, given the corresponding gradient table. The results are a set of tensor images, DWI, ADC and FA maps.
For DSI, odf_recon is used directly to generate a odf file and a max file, as well as a few maps. At this point our DSI recon program only takes pre-calculated recon matrices, corresponding to pre-defined gradient tables.
For HARDI/Q-Ball, users are allowed to provide a customized gradient table (just like for DTI). hardi_mat must be called first to generate the corresponding recon matrix, then odf_recon takes that recon matrix and reconstructs raw images to odf and maps.

3. Fiber tracking. Takes the reconstructed data and generated a track file.

For DTI, dti_tracker is used.
For DSI/HARDI/Q-Ball, odf_tracker is used.

4. Smooth the tracks. spline_filter takes the generated track file from last step and smooth the tracks with a B-Spline filter. This step is not required but strongly recommended. It would remove redundant track points and segments (thus reducing the size of the track file) and also make tracks nicely smoothed. It will NOT change the quality of the tracks or lose any original information.

一、基本设置及常规界面

基于Linux版本，安装方法到官网下载，然后解压出来，直接 cd到相应目录下启动，./trackvis是图形化界面，./track_vis是命令行操作。

点击load加载 *.trk结尾的文件，记得去掉Slice filter中的Y轴过滤选项。

利用鼠标左键旋转，右键缩放，滚轮移动之类的比较简单，自己摸索，这里我就不多说了。

找不到的时候进入toolbar，选择View-reset即可。

二、加载三维图像（以FA图像为例）

单击这个button，就可以打开一幅Image加载到Tracking的结果上。

这里我们加载一幅FA图像上去观察效果：

可以很明显的看到，当选择的FA维度与tracking结果的维度没有差异的时候，两者可以很好的overlay.

左下角的三个勾选框可以选择是否显示该断层的Image信息，同时可以对透明度进行设置。

三、自由绘制一个ROI

通过TrackGroup->New track group from sphere功能，我们可以从特定体素绘制一个roi（也就是说如果我们知道FMRI中出现的一个异常坐标，或者任何的MNI152空间下的异常点坐标，我们都可以在TrackVis中将它标记出来并观察经过这个点的纤维变化情况。）

在OverView中右键点击Trackk Groups中的Track1,Track2，我们就可以把不想看的TrackGroup去掉，比如如果我们只想看经过上述（63，57,33）体素点的坐标，我们就可以把Track1和Track2都Hide掉（这里不要管Track2，Track2是我实验用的），这样就可以得到如下的结果：