DocumentCode :
2796729
Title :
Feature-similarity visualization of MRI cortical surface data
Author :
Bowman, Ian ; Joshi, Shantanu H. ; Greer, V. ; van Horn, John D.
Author_Institution :
Sch. of Med., Lab. of Neuro Imaging, UCLA, Los Angeles, CA, USA
fYear :
2012
fDate :
14-19 Oct. 2012
Firstpage :
211
Lastpage :
212
Abstract :
We present an analytics-based framework for simultaneous visualization of large surface data collections arising in clinical neuroimaging studies. Termed Informatics Visualization for Neuroimaging (INVIZIAN), this framework allows the visualization of both cortical surfaces characteristics and feature relatedness in unison. It also uses dimension reduction methods to derive new coordinate systems using a Jensen-Shannon divergence metric for positioning cortical surfaces in a metric space such that the proximity in location is proportional to neuroanatomical similarity. Feature data such as thickness and volume are colored on the cortical surfaces and used to display both subject-specific feature values and global trends within the population. Additionally, a query-based framework allows the neuroscience researcher to investigate probable correlations between neuroanatomical and subject patient attribute values such as age and diagnosis.
Keywords :
biomedical MRI; data reduction; data visualisation; feature extraction; image retrieval; medical image processing; neurophysiology; INVIZIAN; Jensen-Shannon divergence metric; MRI cortical surface data; analytics-based framework; clinical neuroimaging studies; coordinate systems; cortical surfaces characteristic visualization; dimension reduction methods; feature data; feature relatedness visualization; feature-similarity visualization; informatics visualization-for-neuroimaging; neuroanatomical similarity; query-based framework; subject patient attribute values; surface data collection visualization; Alzheimer´s disease; Brain; Data visualization; Magnetic resonance imaging; Market research; Neuroimaging; I.3 [Computer Graphics]; I.3.3 [Viewing Algorithms]; I.3.8 [Applications]; Three-Dimensional Graphics and Realism;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Analytics Science and Technology (VAST), 2012 IEEE Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4673-4752-5
Type :
conf
DOI :
10.1109/VAST.2012.6400548
Filename :
6400548
Link To Document :
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