Difference between revisions of "CSVfilesDescription"

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   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of Fractional Anisotropy (FA)  
 
   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of Fractional Anisotropy (FA)  
   for trajectory r corresponding to sample c.   
+
   for trajectory r corresponding to sample c of the cluster centerline.   
  
 
   [prefix]_MD_cluster[clusterID].csv
 
   [prefix]_MD_cluster[clusterID].csv
 
    
 
    
 
   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of Mean Diffusivity (MD)  
 
   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of Mean Diffusivity (MD)  
   for trajectory r corresponding to sample c.   
+
   for trajectory r corresponding to sample c of the cluster centerline.   
  
 
   [prefix]_Par_cluster[clusterID].csv
 
   [prefix]_Par_cluster[clusterID].csv
 
    
 
    
 
   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of parallel diffusivity (largest Eigen value of the tensor matrix)
 
   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of parallel diffusivity (largest Eigen value of the tensor matrix)
   for trajectory r corresponding to sample c.   
+
   for trajectory r corresponding to sample c of the cluster centerline.   
  
 
   [prefix]_Per_cluster[clusterID].csv
 
   [prefix]_Per_cluster[clusterID].csv
 
    
 
    
 
   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of perpendicular diffusivity (mean value of the two Eigen values  
 
   A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of perpendicular diffusivity (mean value of the two Eigen values  
   - other than the largest one - of the tensor matrix) for trajectory r corresponding to sample c.
+
   - other than the largest one - of the tensor matrix) for trajectory r corresponding to sample c of the cluster centerline.
  
  
 
Matlab scripts [http://www.nitrc.org/plugins/scmsvn/viewcvs.php/QuantitativeDiffusionTools/trunk/ProcessingScripts/?root=quantitativedti here] can be used to generate plots of diffusion parameters along each cluster.
 
Matlab scripts [http://www.nitrc.org/plugins/scmsvn/viewcvs.php/QuantitativeDiffusionTools/trunk/ProcessingScripts/?root=quantitativedti here] can be used to generate plots of diffusion parameters along each cluster.

Latest revision as of 19:55, 24 November 2009

Home < CSVfilesDescription

For each cluster, the EM Clustering Module generates a set of CSV files. Let’s first define a couple of terms:

N_[clusterID] : number of significant trajectories that belong to cluster [clusterID].

L_[clusterID] : number of samples along the cluster centerline.

'-1': the missing data.

Now, the description of each file is as follows:


 [prefix]_posterior[clusterID].csv
 
  A single column (N_[clusterID] x 1) whose each element is the membership probability of a trajectory in that cluster.
 [prefix]_FA_cluster[clusterID].csv
  
  A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of Fractional Anisotropy (FA) 
  for trajectory r corresponding to sample c of the cluster centerline.  
 [prefix]_MD_cluster[clusterID].csv
  
  A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of Mean Diffusivity (MD) 
  for trajectory r corresponding to sample c of the cluster centerline.  
 [prefix]_Par_cluster[clusterID].csv
  
  A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of parallel diffusivity (largest Eigen value of the tensor matrix)
  for trajectory r corresponding to sample c of the cluster centerline.  
 [prefix]_Per_cluster[clusterID].csv
  
  A matrix (N_[clusterID] x L_[clusterID]) whose each element(r,c) is the value of perpendicular diffusivity (mean value of the two Eigen values 
  - other than the largest one - of the tensor matrix) for trajectory r corresponding to sample c of the cluster centerline.


Matlab scripts here can be used to generate plots of diffusion parameters along each cluster.