CSVfilesDescription - Revision history

Mmaddah at 19:55, 24 November 2009

2009-11-24T19:55:53Z

Mmaddah at 19:16, 24 November 2009

2009-11-24T19:16:34Z

Mmaddah: Created page with '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 …'

2009-11-24T19:10:04Z

Created page with '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 …'

New page

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.

[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.

[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.

[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.

← Older revision		Revision as of 19:16, 24 November 2009
Line 33:		Line 33:
	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.
		+
		+
		+	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.

@@ Line 17: / Line 17: @@
     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
     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
     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
     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.