Literature DB >> 24203652

Graphical neuroimaging informatics: application to Alzheimer's disease.

John Darrell Van Horn1, Ian Bowman, Shantanu H Joshi, Vaughan Greer.   

Abstract

The Informatics Visualization for Neuroimaging (INVIZIAN) framework allows one to graphically display image and meta-data information from sizeable collections of neuroimaging data as a whole using a dynamic and compelling user interface. Users can fluidly interact with an entire collection of cortical surfaces using only their mouse. In addition, users can cluster and group brains according in multiple ways for subsequent comparison using graphical data mining tools. In this article, we illustrate the utility of INVIZIAN for simultaneous exploration and mining a large collection of extracted cortical surface data arising in clinical neuroimaging studies of patients with Alzheimer's Disease, mild cognitive impairment, as well as healthy control subjects. Alzheimer's Disease is particularly interesting due to the wide-spread effects on cortical architecture and alterations of volume in specific brain areas associated with memory. We demonstrate INVIZIAN's ability to render multiple brain surfaces from multiple diagnostic groups of subjects, showcase the interactivity of the system, and showcase how INVIZIAN can be employed to generate hypotheses about the collection of data which would be suitable for direct access to the underlying raw data and subsequent formal statistical analysis. Specifically, we use INVIZIAN show how cortical thickness and hippocampal volume differences between group are evident even in the absence of more formal hypothesis testing. In the context of neurological diseases linked to brain aging such as AD, INVIZIAN provides a unique means for considering the entirety of whole brain datasets, look for interesting relationships among them, and thereby derive new ideas for further research and study.

Entities:  

Mesh:

Year:  2014        PMID: 24203652      PMCID: PMC4012008          DOI: 10.1007/s11682-013-9273-9

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  38 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2010-02-22       Impact factor: 11.205

7.  Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls.

Authors:  Jason P Lerch; Jens Pruessner; Alex P Zijdenbos; D Louis Collins; Stefan J Teipel; Harald Hampel; Alan C Evans
Journal:  Neurobiol Aging       Date:  2006-11-13       Impact factor: 4.673

8.  Cancer biomarker discovery: the entropic hallmark.

Authors:  Regina Berretta; Pablo Moscato
Journal:  PLoS One       Date:  2010-08-18       Impact factor: 3.240

9.  Visual systems for interactive exploration and mining of large-scale neuroimaging data archives.

Authors:  Ian Bowman; Shantanu H Joshi; John D Van Horn
Journal:  Front Neuroinform       Date:  2012-04-23       Impact factor: 4.081

10.  Quantifying collective attention from tweet stream.

Authors:  Kazutoshi Sasahara; Yoshito Hirata; Masashi Toyoda; Masaru Kitsuregawa; Kazuyuki Aihara
Journal:  PLoS One       Date:  2013-04-30       Impact factor: 3.240

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