
  Section of Biomedical Image Analysis
  Department of Radiology
  University of Pennsylvania
  3600 Market Street, Suite 380
  Philadelphia, PA 19104

  Web:   http://www.rad.upenn.edu/sbia/
  Email: sbia-software at uphs.upenn.edu

  Copyright (c) 2012, University of Pennsylvania. All rights reserved.
  See http://www.rad.upenn.edu/sbia/software/license.html or COPYING file.



INTRODUCTION
============

  This software package implements ODVBA [1], which is used to determine the
  optimal spatially adaptive smoothing of images, followed by applying a
  voxel-based group analysis.

  Voxel-based Analysis and Statistical Parametric Mapping (VBA-SPM) [2] of
  imaging data have offered the potential to analyze structural and functional
  data in great spatial detail, without the need to define a priori regions of
  interest (ROIs) and assumptions. Gaussian smoothing of images is an important
  step in VBA-SPM; it accounts for registration errors and integrates imaging
  signals from a region around each voxel being analyzed. However, it has also
  become a limitation of VBA-SPM based methods, since it is often chosen
  empirically, non-optimally, and lacks spatial adaptivity to the shape and
  spatial extent of the region of interest.

  ODVBA provides a mathematically rigorous framework for determining the optimal
  spatial smoothing of structural and functional images, prior to applying
  voxel-based group analysis. In order to determine the optimal smoothing kernel,
  a local discriminative analysis, restricted by appropriate nonnegativity
  constraints, is applied to a spatial neighborhood around each voxel, aiming to
  find the direction best highlights the difference between two groups in that
  neighborhood. Since each voxel belongs to a large number of such neighborhoods,
  each centered on one of its neighboring voxels, the group difference at each
  voxel is determined by a composition of all these optimal smoothing directions.
  Permutation tests are used to obtain the statistical significance of the
  resulting Optimally-Discriminative VBM (ODVBA) maps.



PACKAGE OVERVIEW
================

  Source Package
  --------------

  - BasisProject.cmake   Meta-data used by BASIS to configure the project.
  - CMakeLists.txt       Root CMake configuration file.
  - doc/                 Software documentation such as the user manual.
  - example/             Example input files, including randomly selected data
                         from ADNI [3] to demonstrate the usage of this software.
  - include/             Public header files of libraries.
  - src/                 Source code files.
  - test/                Implementation of software tests and corresponding data.

  - AUTHORS.txt          A list of the people who contributed to this software.
  - COPYING.txt          The copyright and license notices.
  - INSTALL.txt          Build and installation instructions.
  - README.txt           This readme file.


  Binary Package
  --------------

  Please refer to the INSTALL file for details on where the built executables
  and libraries, the auxiliary data, and the documentation files are installed.



LICENSING
=========

  See http://www.rad.upenn.edu/sbia/software/license.html or COPYING file.



INSTALLATION
============

  See build and installation instructions given in the INSTALL file.



DOCUMENTATION
=============

  See the user manual ("ODVBA User Manual.pdf" or "UserManual.pdf")
  for details on the software and an example application of how to apply the
  software tools provided by this package.



REFERENCES
==========

  [1] T. Zhang, C. Davatzikos,
      Optimally-Discriminative Voxel-Based Analysis,
      Proceeding of International Conference on Medical Image Computing and
      Computer-Assisted Intervention, vol. 13, no.2, pp: 257-265 (2010)

  [2] Ashburner, J., Friston, K.J.,
      Voxel-based morphometry-the methods,
      Neuroimage, 11(6) 805–821 (2000)

  [3] Alzheimer’s Disease Neuroimaging Initiative,
      http://www.loni.ucla.edu/ADNI
