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开源软件名称(OpenSource Name):spm/spm12开源软件地址(OpenSource Url):https://github.com/spm/spm12开源编程语言(OpenSource Language):MATLAB 89.2%开源软件介绍(OpenSource Introduction):
This README gives a brief introduction to the SPM software. Full details can be found on the SPM website. See also SPMStatistical Parametric Mapping refers to the construction and assessment of spatially extended statistical process used to test hypotheses about functional imaging data. These ideas have been instantiated in software that is called SPM. The SPM software package has been designed for the analysis of brain imaging data sequences. The sequences can be a series of images from different cohorts, or time-series from the same subject. The current release is designed for the analysis of fMRI, PET, SPECT, EEG and MEG. Please refer to this version as "SPM12" in papers and communications. SPM was written to organise and interpret our data (at The Wellcome Centre for Human Neuroimaging). The distributed version is the same as that we use ourselves. SPM is made freely available to the [neuro]imaging community, to promote collaboration and a common analysis scheme across laboratories. SoftwareThe SPM software is a suite of MATLAB functions, scripts and data files, with some externally compiled C routines, implementing Statistical Parametric Mapping. MATLAB, a commercial engineering mathematics package, is required to use SPM. MATLAB is produced by MathWorks, Natick, MA, USA. SPM requires only core MATLAB to run (no special toolboxes are required). SPM12 is written for MATLAB version 7.4 (R2007a) onwards under Windows, Linux and Mac (SPM12 will not work with versions of MATLAB prior to 7.4). Binaries of the external C-MEX routines are provided for Windows, Linux and Mac. The source code is supplied and can be compiled with a C compiler (Makefile provided). See https://www.fil.ion.ucl.ac.uk/spm/software/spm12/ for details. Later versions of MATLAB (released after SPM12), will probably need additional patches in order to run. Once developed, these will be made available from: https://www.fil.ion.ucl.ac.uk/spm/download/spm12_updates/ Although SPM12 will read image files from previous versions of SPM, there are differences in the algorithms, templates and models used. Therefore, we recommend you use a single SPM version for any given project. The SPM12 Release Notes can be found online: https://www.fil.ion.ucl.ac.uk/spm/software/spm12/ File formatSPM12 uses the NIFTI-1 data format as standard. Take a look at https://nifti.nimh.nih.gov/ for more information on the NIFTI-1 file format. The old SPM2 version of Analyze format can be read straight into SPM12, but results
will be written out as NIFTI-1. If you still use this format, then it is important
that you ensure that The MINC and ECAT7 formats can not be read straight into SPM12, although conversion utilities have been provided. Similarly, a number of DICOM flavours can also be converted to NIFTI-1 using tools in SPM12. ResourcesThe SPM website is the central repository for SPM resources: https://www.fil.ion.ucl.ac.uk/spm/ Introductory material, installation details, documentation, course details and patches are published on the site. There is an SPM email discussion list, hosted at [email protected]. The list is monitored by the authors, and discusses theoretical, methodological and practical issues of Statistical Parametric Mapping and SPM. The SPM website has further details: https://www.fil.ion.ucl.ac.uk/spm/support/ Please report bugs to the authors at [email protected]. Peculiarities may actually be features, and should be raised on the SPM email discussion list, [email protected]. AuthorsSPM is developed under the auspices of Functional Imaging Laboratory (FIL), The Wellcome Centre for Human NeuroImaging, in the Queen Square Institute of Neurology at University College London (UCL), UK. SPM94 was written primarily by Karl Friston in the first half of 1994, with assistance from John Ashburner (MRC-CU), Jon Heather (WDoIN), and Andrew Holmes (Department of Statistics, University of Glasgow). Subsequent development, under the direction of Prof. Karl Friston at the Wellcome Department of Imaging Neuroscience, has benefited from substantial input (technical and theoretical) from: John Ashburner (WDoIN), Andrew Holmes (WDoIN & Robertson Centre for Biostatistics, University of Glasgow, Scotland), Jean-Baptiste Poline (WDoIN & CEA/DRM/SHFJ, Orsay, France), Christian Buechel (WDoIN), Matthew Brett (MRC-CBU, Cambridge, England), Chloe Hutton (WDoIN) and Keith Worsley (Department of Statistics, McGill University, Montreal Canada). See We would like to thank everyone who has provided feedback on SPM. Disclaimer, copyright & licencingSPM (being the collection of files given in the manifest in the
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