A pipeline used to vizualize and analyze clarity treated brain images.
[!(https://img.shields.io/pypi/v/clarityviz.svg)](https://pypi.python.org/pypi/clarityviz/0.0.1) [![Build Status](https://travis-ci.org/alee156/clviz.svg?branch=master)](https://travis-ci.org/alee156/clviz)
clviz is a Python 2 package for Clarity brain analysis. It supports ANALYZE (plain, SPM99, SPM2 and later), GIFTI, NIfTI1, NIfTI2, MINC1, MINC2, MGH and ECAT as well as Philips PAR/REC.
To install the prerequisite packages, clone the directory using: ` git clone https://github.com/alee156/clviz.git cd clviz pip install -r requirements.txt `
After installing the prerequisites there’s two options for using clviz. You can use clviz as a standalone package and perform basic analysis on your own files, or you can install ndreg and ndio and use clviz as a powerful integrating tool for graph-based analysis.
` pip install clarityviz `
## Docker Installation ` docker pull lkzhu1/ubuntu:prototype1 docker run -t -i lkzhu1/ubuntu:prototype1 `
## Getting Started
In development but tutorials will be uploaded shortly!
Complete documentation is located at https://neurodatadesign.github.io/seelviz//reveal/clarityviz.m.html.
Credit to installation script in .travis.yml goes to https://github.com/milq/scripts-ubuntu-debian.