关于用统计分析模块分析VMHC结果的疑问

结果如下:DLH 0.091699 voxels^-3 before correcting for temporal DOF

 

FWHMx = 3.744741 voxels

FWHMy = 3.687451 voxels

FWHMz = 3.645997 voxels

FWHMx = 11.234224 mm

FWHMy = 11.062353 mm

FWHMz = 10.937990 mm

DLH = 0.092841

VOLUME = 174972

RESELS = 50.345928

尊敬的严博士,关于这些结果我不是很明白,我想了解一下上面这些结果分别表示什么意思?感谢亲爱的严博士

Forums:

这是你图像的平滑程度,大概是多少个体素,或者换一个单位是多少mm。

1,我明白了,我的统计结果是指统计结束后在输出路径里生成的T2.nii_Cohen_f2.nii文件和T2.nii文件,那下一步在视图模块进行结果报告的时候,在覆盖中选择这两个文件中的哪一个?这两个文件有什么区别吗?

2,在文献中提到提取每个被试全脑VMHC值与临床量表进行相关分析,我想知道用什么工具可以提取每个被试全脑VMHC值,那这个工具是基于zVMHCMap_sub_002.nii还是基于VMHCMap_sub_002.nii进行数据提取?如果我分别得到了患者组与健康组每个被试的VMHC值,接下来我是用两者的差值与临床量表来进行相关分析,还是直接用患者组每个被试VMHC值与临床量表进行相关分析?

3,以下是我在 JiscMail上看到的一个提取数据的代码:

dear marc.

i encountered the same question a few days ago. 

- if you would like to compare the volume of gray or white matter in total
between two or more groups, you have to extract the data with help of an vbm
tool (maybe dartel or vbm 5.1 in spm5) from the normalized and modulated
tissue images (either gray or white matter). in vbm 5.1 there is a simple
tool under the options which extracts the volumes for each subject
separately. maybe you should look in the manual.

- if you would like to compare the volumes of gray matter between two groups
for a specified ROI, john ashburner provided me with a very helpful script
to extract those. For this you should habe a binary (o,1) mask for your Roi
which is used to extract the data from the modulated and normalized gray
matter images. the script is as follows. just copy this into matlab and
follow the instructions. the output is in litre.

good luck

markus

Vmask  = spm_vol(spm_select(1,'image','Select the binary mask')); Vdata  =
spm_vol(spm_select(Inf,'image','Select modulated warped GM')); volume =
zeros(numel(Vdata),1);

for j=1:numel(Vdata),
    tot = 0;
    for i=1:Vdata(j).dim(3),
        M    = spm_matrix([0 0 i]);
        img  = spm_slice_vol(Vdata(j),M,Vdata(j).dim(1:2),0);
        Mmsk = Vmask.mat\Vdata(j).mat*M;
        mask = spm_slice_vol(Vmask,Mmsk,Vdata(j).dim(1:2),0);
        img  = img.*mask;
        img(~isfinite(img)) = 0;
        tot = tot + sum(img(:));
    end
    voxvol    = abs(det(Vdata(j).mat))/100^3;
    volume(j) = tot*voxvol;
end

disp(volume)

有个网友告诉我这个代码改改后可以用来计算每个被试全脑的VMHC值,但我完全不懂代码,我想请教下严老师,可以帮我改改这个代码吗?呜呜呜

仔细看rfmri.org/course下关于Viewer和Utilities->ROI Signals Extractor的部分。