Graphical neuroimaging informatics: application to Alzheimer's disease.
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 corti...
| Publicado en: | Brain Imaging & Behavior Vol. 8; no. 2; pp. 300 - 311 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jun2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103821357&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103821357 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 19317557 3GSC jtl: Brain Imaging & Behavior issn: 19317557 maglogo: N pubinfo: dt: Jun2014 vid: 8 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 103821357 NLM24203652 2012571235 10.1007/s11682-013-9273-9 NLM24203652 PMC4012008 103821357 ppf: 300 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Graphical neuroimaging informatics: application to Alzheimer's disease. aug: au: Van Horn, John Darrell Bowman, Ian Joshi, Shantanu H Greer, Vaughan affil: The Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 North Soto Street - SSB1-102, Los Angeles, CA, 90032, USA, jvanhorn@usc.edu. sug: subj: Alzheimer's Disease Pathology Brain Pathology Data Mining Methods Image Processing, Computer Assisted Methods Cognition Disorders Neuroradiography Methods Aged Aging Cerebral Cortex Pathology Resource Databases Gray Matter Pathology Hippocampus Pathology Magnetic Resonance Imaging Methods Body Weights and Measures User-Computer Interface Aged: 65+ years ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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