The dMRI data processing toolbox PANDA v1.3.0 was releasedPosted By: Zaixu Cui - Aug 26, 2015
Tool/Resource: PANDA: a pipeline tool for diffusion MRI
The diffusion MRI data processing toolbox PANDA v1.3.0 (http://www.nitrc.org/projects/panda/) was released.
PANDA (Pipeline for Analyzing braiN Diffusion imAges) is a matlab toolbox for pipeline processing of diffusion MRI images. For each subject, PANDA can provide outputs in 2 types: i) diffusion parameter data that is ready for statistical analysis; ii) brain anatomical networks constructed by using diffusion tractography. Particularly, there are 3 types of resultant diffusion parameter data: WM atlas-level, voxel-level and TBSS-level. The brain network generated by PANDA has various edge definitions, e.g. fiber number, length, FA or probability-weighted.
Some new features were added in this version:
I. Improvements in data analysis
1. Using the average of all the B0 images as reference for eddycurrent correction.
2. Statistical analysis and results display GUI for TBSS analysis.
3. Combining TBSS and white matter atlas to calculate the average value of skeleton image in each ROI, the results can be statistically analysed using SPSS.
4. T1 template can be defined by the user in the network node definition part.
II. New Utilities
1. Utility Cluster Locator for localizing the statistically significant areas.
2. Utility White Matter Mask for calculating white matter mask using FA images of all subjects.
3. Utility ROI-mask Extractor for extracting ROI from prior atlas.
4. Utility Between-atlas Mapping for mapping high-resolution atlas to anatomical atlas, such as mapping random 1024 atlas to the 90 AAL atlas.
5. Utility ROI-mean Extractor for calculating average value of an image in the mask.
6. Utility Merge NIfTI for merging multiple 3D images into a 4D image.
7. Utility Image Smoother for smoothing NIFTI images.
8. Adding two parameters (-S: eye & optic nerve cleanup, and –B: bias field & neck cleanup) for Utility Brain Extraction (T1).
1. Fixing some bugs in previous version
2. Writing a detailed manual document which elaborates the questions asked by the users before.