TY - GEN
T1 - Fusion of structural and functional cardiac magnetic resonance imaging data for studying Ventricular Fibrillation
AU - Magtibay, K.
AU - Beheshti, M.
AU - Foomany, F. H.
AU - Balasundaram, K.
AU - Masse, S.
AU - Lai, P.
AU - Asta, J.
AU - Zamiri, N.
AU - Jaffray, D. A.
AU - Nanthakumar, K.
AU - Krishnan, S.
AU - Umapathy, K.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/2
Y1 - 2014/11/2
N2 - Magnetic Resonance Imaging (MRI) techniques such as Current Density Imaging (CDI) and Diffusion Tensor Imaging (DTI) provide a complementing set of imaging data that can describe both the functional and structural states of biological tissues. This paper presents a Joint Independent Component Analysis (jICA) based fusion approach which can be utilized to fuse CDI and DTI data to quantify the differences between two cardiac states: Ventricular Fibrillation (VF) and Asystolic/Normal (AS/NM). Such an approach could lead to a better insight on the mechanism of VF. Fusing CDI and DTI data from 8 data sets from 6 beating porcine hearts, in effect, detects the differences between two cardiac states, qualitatively and quantitatively. This initial study demonstrates the applicability of MRI-based imaging techniques and jICA-based fusion approach in studying cardiac arrhythmias.
AB - Magnetic Resonance Imaging (MRI) techniques such as Current Density Imaging (CDI) and Diffusion Tensor Imaging (DTI) provide a complementing set of imaging data that can describe both the functional and structural states of biological tissues. This paper presents a Joint Independent Component Analysis (jICA) based fusion approach which can be utilized to fuse CDI and DTI data to quantify the differences between two cardiac states: Ventricular Fibrillation (VF) and Asystolic/Normal (AS/NM). Such an approach could lead to a better insight on the mechanism of VF. Fusing CDI and DTI data from 8 data sets from 6 beating porcine hearts, in effect, detects the differences between two cardiac states, qualitatively and quantitatively. This initial study demonstrates the applicability of MRI-based imaging techniques and jICA-based fusion approach in studying cardiac arrhythmias.
KW - Data Fusion
KW - Joint Independent Component Analysis
KW - Magnetic Resonance Imaging
KW - Ventricular Fibrillation
UR - http://www.scopus.com/inward/record.url?scp=84929484816&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84929484816&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2014.6944891
DO - 10.1109/EMBC.2014.6944891
M3 - Conference contribution
C2 - 25571259
AN - SCOPUS:84929484816
T3 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
SP - 5579
EP - 5582
BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Y2 - 26 August 2014 through 30 August 2014
ER -