trislett/tmi_viewer

Neuroimaging Viewer for TMI files to be used with TFCE_mediation (https://github.com/trislett/TFCE_mediation)

TMI_Viewer: Vertex/Voxel Rendering for TMI files and other neuroimaging formats

The tmi_viewer package contains two programs:

A) tmi_viewer

Displays multimodal neuroimaging data (surfaces and volumes) in the same space from a TMI file (although TMI files are not required).

Features:

• Multiple surfaces with vertex painting can be easily viewed with voxel images.
• Voxel images can be viewed as: (1) surfaces using a marching cube algorithm, (2) voxel contour, (3) and voxel scalar field.
• The default settings are optimized for viewing neuroimages.
• tmi_viewer is highly optimized for speed.
• Many autothresholding algorithms available including: Otsu et al., Li et al., Yen et al., and Z threholding.
• Extremely fast algorithm for applying Lapacian or Taubin (low-pass) smooth. e.g., ~1000 passes takes around one minute.
• Easy export of background transparent images for creating figures.
• Many new look-up tables (LUTs) that are specifically designed for visualising neuroimaging statistics (as well as the LUTs included with matplotlib).

B) tm_slices

Outputs a web-page with whole brain slices from voxel-based neuroimages in native coordinates with optional overlaps.

Features:

• Great for making figures: Creates a web-page displaying overlapping any number of voxel-based images, and they can be at any resolution.
• Many autothresholding algorithms available including: Otsu et al., Li et al., Yen et al., and Z threholding.
• Import images, binarize them at any threshold, and paint the image outline.
• Specify number of slices, size of slices, transparency, etc.

Installation

With sudo permissions

Requirements:

• TFCE_mediation
• VTK

For Ubuntu: sudo apt-get install vtk6 python-vtk python-qt4

For OSX: brew install vtk

Installation:

Using PIP (Recommended): sudo -H pip install -U tmi_viewer

From source: sudo python setup.py install

• Additional requirement: mayavi

Using a Python Virtual Environment

Note: this example uses python 3.5

Create and source virtual environment

virtualenv -p python3.5 python3env
source python3env/bin/activate

Install TFCE_mediation

pip install -U tfce-mediation

Download and install SIP and PyQT4

a. Download and unzip SIP and PyQT4

• SIP download link
• QT4 download link

b. Install SIP (not version may be different)

cd sip-4.19.7
python configure.py
make
make install

c. Install PyQT4

cd ../PyQt-x11-gpl-4.12.1
python configure-ng.py

Accepted the user agreement then run:

make
make install

pip install vtk

pip install vtk

pip install tmi_viewer

pip install -U tmi_viewer

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These programs relies on Mayavi, and setting can changed using the Mayavi interactive session. If you use them please cite:

Ramachandran, P. and Varoquaux, G., Mayavi. 3D Visualization of Scientific Data. IEEE Computing in Science & Engineering, 13 (2), pp. 40-51 (2011).

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