DPARSF

您好，我用dparsf得到alff结果进行两样本t检验时发现还有脑室内的信号增强还有很多undefined的脑区（自己做的mask和brainmask均有），这时候应该怎么处理？
另外，利用两组数据单样本t检验结果做mask的表达式是不是(i1>0)+(i2>0)>0，用~表示不等于 image calculator出错，求准确表达式
不胜感激！

亲爱滴们：

今天碰到这样一个问题，焦头烂额：
由于这批数据需要手动配准，所以我的处理流程如下：
1. 用dparsf批处理至realign。
2.用spm做coregister.
3.用AFNI转换格式后做Normalize
4.转换个格式后，将得到的EPI相文件放入FunImgNormalized文件夹。
然后启动dparsf，
先跳过Smooth做的ReHo，很顺利，detrend, filter, reho...没有任何问题。
然后继续用dparsf做alff以及falff，操作过程如下：
    -matlab下输入dparsf
    -依次去掉smooth前所有的勾
    -选择工作目录
   - 输入时间点190
   - 选择自定义模板 

hi,

the previous error i brought up was fixed by adding the line
    "rest_Fix_Read_Write_Error"
before initializing dparsf.

however, the time between pressing the bottom "run" and actual data precessing is much longer  in the linux environment than windows (just now i experienced a 15 min lag).
so is the time for data precessing.
what might the problem be? how can i fix it?
i'm currently using double systems on my laptop, which are windows XP and linux fedora ver 12.

Hello, Dear DPARSF team

I ran into some problems when I try to compute functional connectivity when using DPARSF. It gave me error message as following. I tried REST to do FC analysis and got same error message. And it is apparently not due to different preprocessing because I used DPARSF to do the preprocessing. Would you please help me solve the problem? Thanks a lot for your help in advance.

 Dear RESTers:

Recently I used DPARSF to process some functional images obtained from GE HDx 3.0T system, my environment was Ubuntu 9.10 AMD 64 Version, Matlab 2009b, SPM8 and DPARSF 100510.

During converting Dicom to nii step, the system keeps running but nothing was converted from dicom files. 

Maybe it's a bug of DPARSF with linux, all the images were smoothly process in WinXP.

Best

Lin 

我利用 DPARSF 来预处理我的功能像数据，每个患者有 3 个 session，因此我将 FunRaw 里面设置为 subject001_1、subject001_2、subject001_3...，而T1Raw里面相应的放上 3 个 subject001 的 3D 结构像、然后 subject002...
前面的步骤运行顺利，但是到 smooth 的时候，报了错，并且文件夹中未生成用于检验 normalization 效果的图像文件夹。
系统为win xp，spm8，刚更新了DPARSF 和 REST1.4，报错信息如下：

通过患者组和正常受试者组的双样本 T 检验，找到了一些患者 ALFF 出现明显异常的区域。现在我想做这个明显异常区域中的 ALFF time course 与临床指标之间的相关性分析，我的做法如下：

• 利用 add recursively all subfolders 加入了每一名患者的 detrended_filtered 静息态图像
• 使用 user defined mask file 添加进一个我利用 rest slice viewer 保存的 ROI 图像。

输出的文件是每个被试一个 mat 文件，里面有 200 个 time course 文件（应该是对应的 200 个时间点的图像）。

我的问题：

我注意到我的 DPARSF 在计算 ReHo 的时候，在 Matlab 的命令窗口给出了这样的信息：

Read these 3D EPI functional images.    wait...
     Read 3D EPI functional images: "/home/yun/fMRI/Rest/FunImgNormalizedDetrendedFiltered/Subject001".........................................

     Calculate the rank of time series on voxel by voxelWarning: Conversion rounded non-integer floating point value to nearest uint16 value.
> In reho at 139
  In DPARSF_run at 607

没能预定到听课的座位，非常可惜，还好有新的视频教程，看了两遍后试着处理了一下目前的患者数据，把自己的步骤和过程放上来请大家看看，是否存在什么问题。

1. 运行环境：Ubuntu 9.10 AMD64 + Matlab R2009b + REST2007V1.3_091215 + DPARSF_V1.0_091215 + SPM8 (patched to 3408)

Data Processing Assistant for Resting-State fMRI (DPARSF) is a convenient plug-in software based on SPM and REST. You just need to arrange your DICOM files, and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, nomalize, smooth) data, FC, ReHo, ALFF and fALFF results. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. You can use DPARSF to extract AAL or ROI time courses (or extract Gray Matter Volume of AAL regions, command line only) efficiently if you want to perform small-world analysis. This software is very easy to use, just click on buttons if you are not sure what it means, popup tips would tell you what you need to do. You also can download a MULTIMEDIA COURSE to know more about how to use this software. Add DPARSF's directory to MATLAB's path and enter "DPARSF" in the command window of MATLAB to enjoy it. The latest release is DPARSF_V1.0_100510.  DOWNLOAD  Multimedia Course: Data Processing of Resting-State fMRI

New features of DPARSF_V1.0_100510:
1. Added a right-click menu to delete all the participants' ID.
2. Fixed a bug in converting DICOM files to NIfTI in Windows 7, thanks to Prof. Chris Rorden's new dcm2nii.
3. Now will detect if co* T1 image (T1 image which is reoriented to the nearest orthogonal direction to 'canonical space' and removed excess air surrounding the individual as well as parts of the neck below the cerebellum) exists before normalization by using T1 image unified segmentation. T1 image without 'co' is also allowed in the analysis now.

New features of DPARSF_V1.0_100420:
1. After extracting ROI time courses, not just functional connectivity will be calculated, but also transform the r values to z values by Fisher's z transformation.
2. Fixed a bug in generating pictures for checking normalization when the bounding box is not [-90 -126 -72;90 90 108].