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| 1 | +--- |
| 2 | +layout: default |
| 3 | +title: Chapter_01_Getting_Started_with_NFT |
| 4 | +long_title: Chapter_01_Getting_Started_with_NFT |
| 5 | +parent: NFT |
| 6 | +grand_parent: Plugins |
| 7 | +--- |
| 8 | +Introduction |
| 9 | +------------ |
| 10 | + |
| 11 | +The Neuroelectromagnetic Forward Head Modeling Toolbox is an open-source |
| 12 | +software toolbox running under MATLAB (The Mathworks, Inc.) for |
| 13 | +generating realistic head models from available data (MRI and/or |
| 14 | +electrode locations) and for solving the forward problem of |
| 15 | +electro-magnetic source imaging. The toolbox includes tools for |
| 16 | +segmenting scalp, skull, cerebrospinal fluid (CSF) and brain tissues |
| 17 | +from T1-weighted magnetic resonance (MR) images. After extracting the |
| 18 | +segmented tissue volumes, mesh generation can be performed. When MR |
| 19 | +images are not available, it is possible to warp a template head model |
| 20 | +to measured electrode locations to obtain a better-fitting head model. |
| 21 | +The toolbox also includes electrode scalp mesh co-registration and |
| 22 | +generation of a uniform source space inside the brain volume for to be |
| 23 | +used in coarse source localization. The Boundary Element Method (BEM) is |
| 24 | +used for the numerical solution of the forward problem. Toolbox |
| 25 | +functions can be called from either a graphic user interface or from the |
| 26 | +command line. Function help messages and a tutorial are included. The |
| 27 | +toolbox is freely available under the GNU Public License for |
| 28 | +noncommercial use and open source development. |
| 29 | + |
| 30 | +The toolbox uses the following third party tools and libraries for |
| 31 | +segmentation, mesh generation and forward problem solution. The source |
| 32 | +codes for these tools are available. |
| 33 | + |
| 34 | +1\. ASC - for triangulation of 3D volumes. |
| 35 | + |
| 36 | +2\. Qslim - for mesh coarsening. |
| 37 | + |
| 38 | +3\. Matitk - Matlab interface to the ITK image processing toolkit. |
| 39 | + |
| 40 | +4\. Metu-bem - Boundary Element Method solver. |
| 41 | + |
| 42 | +The NFT toolbox provides a user interface (UI) for segmentation, mesh |
| 43 | +generation and for creating the numerical head model. It also has a well |
| 44 | +defined MATLAB command-line interface. |
| 45 | + |
| 46 | +This manual explains how to use the NFT toolbox. The head modeling UI, |
| 47 | +the command line API and the structures are described. An overview of |
| 48 | +the implementation is provided. |
| 49 | + |
| 50 | +The next section describes the installation of the toolbox. The Getting |
| 51 | +Started section provides an overview of the interface. Head modeling |
| 52 | +from 3D MR images is described next, followed by head modeling from |
| 53 | +template warping. This is followed by a section on forward modeling and |
| 54 | +examples. The [final |
| 55 | +section](Chapter_05_NFT_Commands_and_Functions "wikilink") is a |
| 56 | +summary of all toolbox functions and commands. |
| 57 | + |
| 58 | +Installation and Configuration |
| 59 | +------------------------------ |
| 60 | + |
| 61 | +This section describes installation and configuration of the NFT |
| 62 | +Toolbox. The following steps are necessary for a proper installation of |
| 63 | +the toolbox: |
| 64 | + |
| 65 | +1\. Extract or copy the toolbox directory to a suitable place on your |
| 66 | +computer file system. |
| 67 | + |
| 68 | +2\. The extracted directory will contain m-files, and C++ executables. |
| 69 | + |
| 70 | +3\. Add the toolbox directory to the MATLAB path. You can use the File → |
| 71 | +SetPath menu item or the addpath() function. Under linux/unix, you may |
| 72 | +add the directory to the MATLABPATH. |
| 73 | + |
| 74 | +The toolbox can also make use of the Matlab Parallel Processing toolbox |
| 75 | +(if installed) to distribute the computation of the transfer and |
| 76 | +lead-field matrices to multiple processors. To do this, before running |
| 77 | +NFT, the user must simply enter |
| 78 | + |
| 79 | +\>\> matlabpool(n) % where n is the number of compute nodes available |
| 80 | + |
| 81 | +In parallel mode, wait bars do not appear while computing the transfer |
| 82 | +and lead-field matrices. |
| 83 | + |
| 84 | +Getting Started |
| 85 | +--------------- |
| 86 | + |
| 87 | +The toolbox starts by typing |
| 88 | +Neuroelectromagnetic_Forward_Modeling_Toolbox or NFT on command window. |
| 89 | +Main window appears as shown in Figure 1. This window is divided into |
| 90 | +three panels. The first panel is used to select the working folder, and |
| 91 | +to name the subject and the session. The NFM toolbox requires a subject |
| 92 | +folder to be specified at startup. All subject specific output is saved |
| 93 | +into this folder. The filenames are derived from the subject and session |
| 94 | +names entered into this panel. The second panel is the Head modeling |
| 95 | +panel. The head model can either be created from MR images, or a |
| 96 | +template head model can be warped to digitized sensors. The head |
| 97 | +modeling panel provides the following operations when creating a head |
| 98 | +model from MR images: |
| 99 | + |
| 100 | + |
| 101 | + |
| 102 | +**Image Segmentation** |
| 103 | + |
| 104 | + |
| 105 | + |
| 106 | +Interface for tissue classification from 3D MR Images. |
| 107 | + |
| 108 | +**Mesh Generation** |
| 109 | + |
| 110 | + |
| 111 | + |
| 112 | +Uses the segmentation results to generate realistic BEM meshes. |
| 113 | + |
| 114 | +**Source Space Generation** |
| 115 | + |
| 116 | + |
| 117 | + |
| 118 | +Generates a regular grid sources within the brain mesh. |
| 119 | + |
| 120 | +**Electrode Co-Registration** |
| 121 | + |
| 122 | + |
| 123 | + |
| 124 | +Registers digitized electrode locations to the scalp mesh. |
| 125 | + |
| 126 | +When generating a template-based head model from digitized electrode |
| 127 | +positions, the only option is Template Warping. The final panel in the |
| 128 | +main menu is for Forward Model Generation. This opens up the Forward |
| 129 | +Model Generation interface which is used to compute the BEM coefficient |
| 130 | +matrix, create the transfer matrices for each sensor, and generate lead |
| 131 | +field matrices for a source distribution. |
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