A Review on the Bioinformatics Tools for Neuroimaging.

Neuroimaging is a new technique used to create images of the structure and function of the nervous system in the human brain. Currently, it is crucial in scientific fields. Neuroimaging data are becoming of more interest among the circle of neuroimaging experts. Therefore, it is necessary to develop a large amount of neuroimaging tools. This paper gives an overview of the tools that have been used to image the structure and function of the nervous system. This information can help developers, experts, and users gain insight and a better understanding of the neuroimaging tools available, enabling better decision making in choosing tools of particular research interest. Sources, links, and descriptions of the application of each tool are provided in this paper as well. Lastly, this paper presents the language implemented, system requirements, strengths, and weaknesses of the tools that have been widely used to image the structure and function of the nervous system.

[1]  M. Raichle Functional Brain Imaging and Human Brain Function , 2003, The Journal of Neuroscience.

[2]  Arthur W Toga,et al.  The LONI Pipeline Processing Environment , 2003, NeuroImage.

[3]  Jennifer L. Cuzzocreo,et al.  Volumetric neuroimage analysis extensions for the MIPAV software package , 2007, Journal of Neuroscience Methods.

[4]  Karl J. Friston,et al.  Statistical parametric mapping , 2013 .

[5]  Susan L. Whitfield-Gabrieli,et al.  Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks , 2012, Brain Connect..

[6]  AD Gouws,et al.  DataViewer3D: An open-source, cross-platform multi-modal neuroimaging data visualization tool , 2009, NeuroImage.

[7]  Sanjiv S. Gambhir,et al.  AMIDE: A Free Software Tool for Multimodality Medical Image Analysis , 2003 .

[8]  Jan Sijbers,et al.  ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data , 2009 .

[9]  G Lohmann,et al.  LIPSIA--a new software system for the evaluation of functional magnetic resonance images of the human brain. , 2001, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[10]  K Amunts,et al.  Quantitative analysis of sulci in the human cerebral cortex: Development, regional heterogeneity, gender difference, asymmetry, intersubject variability and cortical architecture , 1997, Human brain mapping.

[11]  S. Resnick,et al.  An image-processing system for qualitative and quantitative volumetric analysis of brain images. , 1998, Journal of computer assisted tomography.

[12]  N. Schiff Multimodal Neuroimaging Approaches to Disorders of Consciousness , 2006, The Journal of head trauma rehabilitation.

[13]  Michael R. Ibbotson,et al.  Effects of saccades on visual processing in primate MSTd , 2010, Vision Research.

[14]  C. Jack,et al.  Ways toward an early diagnosis in Alzheimer’s disease: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) , 2005, Alzheimer's & Dementia.

[15]  Xenophon Papademetris,et al.  BioImage Suite: An integrated medical image analysis suite: An update. , 2006, The insight journal.

[16]  Conrad C. Huang,et al.  UCSF Chimera—A visualization system for exploratory research and analysis , 2004, J. Comput. Chem..

[17]  Stephen José Hanson,et al.  Combinatorial codes in ventral temporal lobe for object recognition: Haxby (2001) revisited: is there a “face” area? , 2004, NeuroImage.

[18]  Alan Connelly,et al.  MRtrix: Diffusion tractography in crossing fiber regions , 2012, Int. J. Imaging Syst. Technol..

[19]  Paul A Craig,et al.  A survey of educational uses of molecular visualization freeware , 2013, Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology.

[20]  Richard M. Leahy,et al.  BrainSuite: An Automated Cortical Surface Identification Tool , 2000, MICCAI.

[21]  D. Goodsell,et al.  Visualization of macromolecular structures , 2010, Nature Methods.

[22]  Daniel C. Alexander,et al.  Camino: Open-Source Diffusion-MRI Reconstruction and Processing , 2006 .

[23]  Rainer Goebel,et al.  BrainVoyager — Past, present, future , 2012, NeuroImage.

[24]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[25]  Scott T. Grafton,et al.  Automated image registration: I. General methods and intrasubject, intramodality validation. , 1998, Journal of computer assisted tomography.

[26]  Hans-Christian Hege,et al.  amira: A Highly Interactive System for Visual Data Analysis , 2005, The Visualization Handbook.

[27]  S. Sadigh-Eteghad,et al.  Different patterns of brain activation in normal aging and Alzheimer's disease from cognitional sight: meta analysis using activation likelihood estimation , 2014, Journal of the Neurological Sciences.

[28]  Heping Zhang,et al.  Localizing Value of Ictal–Interictal SPECT Analyzed by SPM (ISAS) , 2005, Epilepsia.

[29]  Milan Sonka,et al.  3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.

[30]  C. Rorden,et al.  Stereotaxic display of brain lesions. , 2000, Behavioural neurology.

[31]  Stefan Pollmann,et al.  PyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data , 2009, Neuroinformatics.

[32]  Mohammad Reza Daliri,et al.  Software Tools for the Analysis of Functional Magnetic Resonance Imaging , 2012 .

[33]  Angela M. Uecker,et al.  ALE meta‐analysis: Controlling the false discovery rate and performing statistical contrasts , 2005, Human brain mapping.

[34]  Jessica A. Turner,et al.  COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets , 2011, Front. Neuroinform..