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AMICO

Implementation of the linear framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) described here:

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data Alessandro Daducci, Erick J. Canales-Rodriguez, Hui Zhang, Tim B. Dyrby, Daniel C. Alexander, Jean-Philippe Thiran , NeuroImage, 2014 (in press)

Installation

Download and install external software

  • NODDI MATLAB toolbox. Download the software and follow the instructions provided here to install it. Be sure to properly include this toolbox in your MATLAB PATH.

  • CAMINO toolkit. Download the software and follow the instructions provided here to install it. NB: be sure to properly update the configuration variable CAMINO_path (see later).

  • SPArse Modeling Software. Download the software and follow the instructions provided here to install it. Be sure to properly include this toolbox in your MATLAB PATH.

Setup paths/variables in MATLAB

Add the folder containing the source code of AMICO to your MATLAB PATH.

Copy the file AMICO_Setup.txt and rename it to AMICO_Setup.m. Modify its content to set the paths to your specific needs:

  • AMICO_code_path : path to the folder containing the source code of AMICO (this repository). E.g. /home/user/AMICO/code.

  • CAMINO_path : path to the bin folder containing the executables of the Camino toolkit (in case you want to use ActiveAx, not needed for NODDI). E.g. /home/user/camino/bin.

  • AMICO_data_path : path to the folder where you store all your datasets. E.g. /home/user/AMICO/data. Then, the software assumes the folder structure is the following:

    ├── data
    ├── Study_01                 --> all subjects acquired with protocol "Study_01"
        ├── Subject_01
        ├── Subject_02
        ├── ...
    ├── Study_02                 --> all subjects acquired with protocol "Study_02"
        ├── Subject_01
        ├── Subject_02
        ├── ...
    ├── ...

    This way, the kernels need to be computed only once per each study, i.e. same protocol (number of shells, b-values etc), and subsequently adapted to each subject (specific gradient directions) very efficiently.

Getting started

Tutorials/demos are provided in the folder doc/demos to help you get started with the AMICO framework.