Myocardial strain computed at multiple spatial scales from tagged magnetic resonance imaging: Estimating cardiac biomarkers for CRT patients

[1]  Alejandro F. Frangi,et al.  Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge , 2018, IEEE Journal of Biomedical and Health Informatics.

[2]  Frank Timmermans,et al.  The electrocardiographic characteristics of septal flash in patients with left bundle branch block , 2016, Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology.

[3]  Daniel Rueckert,et al.  A framework for combining a motion atlas with non‐motion information to learn clinically useful biomarkers: Application to cardiac resynchronisation therapy response prediction , 2017, Medical Image Anal..

[4]  Jack Lee,et al.  Eidolon: Visualization and Computational Framework for Multi-modal Biomedical Data Analysis , 2016, MIAR.

[5]  Nicolas Duchateau,et al.  Infarct localization from myocardial deformation: Prediction and uncertainty quantification by regression from a low-dimensional space. , 2016, IEEE transactions on medical imaging.

[6]  Jack Lee,et al.  Multiphysics and multiscale modelling, data–model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics , 2016, Interface Focus.

[7]  Daniel Rueckert,et al.  A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion , 2015, Medical Image Anal..

[8]  Daniel Rueckert,et al.  Towards Left Ventricular Scar Localisation Using Local Motion Descriptors , 2015, STACOM@MICCAI.

[9]  Daniel Rueckert,et al.  Beyond the AHA 17-Segment Model: Motion-Driven Parcellation of the Left Ventricle , 2015, STACOM@MICCAI.

[10]  Nicolas Duchateau,et al.  Prediction of Infarct Localization from Myocardial Deformation , 2015, STACOM@MICCAI.

[11]  Daniel Rueckert,et al.  Prospective Identification of CRT Super Responders Using a Motion Atlas and Random Projection Ensemble Learning , 2015, MICCAI.

[12]  E. Nagel,et al.  Microsphere skimming in the porcine coronary arteries: Implications for flow quantification. , 2015, Microvascular Research.

[13]  Maxime Sermesant,et al.  Spatio-Temporal Tensor Decomposition of a Polyaffine Motion Model for a Better Analysis of Pathological Left Ventricular Dynamics , 2015, IEEE Transactions on Medical Imaging.

[14]  Lluís Mont,et al.  Mechanical abnormalities detected with conventional echocardiography are associated with response and midterm survival in CRT. , 2014, JACC. Cardiovascular imaging.

[15]  Reza Razavi,et al.  A U-shaped type II contraction pattern in patients with strict left bundle branch block predicts super-response to cardiac resynchronization therapy. , 2014, Heart rhythm.

[16]  Xi Chen,et al.  Gift-Giving and Network Structure in Rural China: Utilizing Long-Term Spontaneous Gift Records , 2014, PloS one.

[17]  Reza Razavi,et al.  Combined identification of septal flash and absence of myocardial scar by cardiac magnetic resonance imaging improves prediction of response to cardiac resynchronization therapy , 2014, Journal of Interventional Cardiac Electrophysiology.

[18]  Yasushi Miyauchi,et al.  Cardiac resynchronization therapy restored ventricular septal myocardial perfusion and enhanced ventricular remodeling in patients with nonischemic cardiomyopathy presenting with left bundle branch block. , 2014, Heart rhythm.

[19]  Feng Liu,et al.  Impact of Etiology on the Outcomes in Heart Failure Patients Treated with Cardiac Resynchronization Therapy: A Meta-Analysis , 2014, PloS one.

[20]  Nicolas Duchateau,et al.  Myocardial motion and deformation patterns in an experimental swine model of acute LBBB/CRT and chronic infarct , 2014, The International Journal of Cardiovascular Imaging.

[21]  D. Kass,et al.  Electromechanical Dyssynchrony and Resynchronization of the Failing Heart , 2013, Circulation research.

[22]  Nicolas Duchateau,et al.  Adaptation of Multiscale Function Extension to Inexact Matching: Application to the Mapping of Individuals to a Learnt Manifold , 2013, GSI.

[23]  Annick Lesne,et al.  Multiscale Analysis of Biological Systems , 2013, Acta biotheoretica.

[24]  Alejandro F. Frangi,et al.  A High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT , 2013, IEEE Transactions on Medical Imaging.

[25]  Alejandro F. Frangi,et al.  Characterization and Modeling of the Peripheral Cardiac Conduction System , 2013, IEEE Transactions on Medical Imaging.

[26]  Alejandro F. Frangi,et al.  Constrained manifold learning for the characterization of pathological deviations from normality , 2012, Medical Image Anal..

[27]  Arthur J Moss,et al.  Predictors of super-response to cardiac resynchronization therapy and associated improvement in clinical outcome: the MADIT-CRT (multicenter automatic defibrillator implantation trial with cardiac resynchronization therapy) study. , 2012, Journal of the American College of Cardiology.

[28]  Alejandro F. Frangi,et al.  SPM to the heart: Mapping of 4D continuous velocities for motion abnormality quantification , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

[29]  Alistair A. Young,et al.  The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart , 2011, Bioinform..

[30]  Alejandro F. Frangi,et al.  A spatiotemporal statistical atlas of motion for the quantification of abnormal myocardial tissue velocities , 2011, Medical Image Anal..

[31]  G. Fishman,et al.  The Cardiac Conduction System , 2011, Circulation.

[32]  Michael I. Miller,et al.  Cardiac motion analysis in ischemic and non-ischemic cardiomyopathy using parallel transport , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[33]  Piet Claus,et al.  Toward understanding response to cardiac resynchronization therapy: left ventricular dyssynchrony is only one of multiple mechanisms. , 2009, European heart journal.

[34]  R. M. Henkelman,et al.  Volume Ordering for Analysis and Modeling of Vascular Systems , 2009, Annals of Biomedical Engineering.

[35]  Alejandro F. Frangi,et al.  Bilinear Models for Spatio-Temporal Point Distribution Analysis , 2009, 2007 IEEE 11th International Conference on Computer Vision.

[36]  F. Crea,et al.  Coronary microvascular dysfunction. , 2013, The New England journal of medicine.

[37]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[38]  Daniel Rueckert,et al.  Construction of a 4D Statistical Atlas of the Cardiac Anatomy and Its Use in Classification , 2005, MICCAI.

[39]  M. Cerqueira,et al.  Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. , 2002, Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology.

[40]  Jacob Fish,et al.  Multiscale analysis of composite materials and structures , 2000 .

[41]  Jerry L Prince,et al.  Cardiac motion tracking using CINE harmonic phase (HARP) magnetic resonance imaging , 1999, Magnetic resonance in medicine.

[42]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[43]  Fionn Murtagh,et al.  Image processing and data analysis , 1998 .

[44]  R. D. Wood,et al.  Nonlinear Continuum Mechanics for Finite Element Analysis , 1997 .

[45]  James H. Brown,et al.  A General Model for the Origin of Allometric Scaling Laws in Biology , 1997, Science.

[46]  Laurent D. Cohen,et al.  Tracking and motion analysis of the left ventricle with deformable superquadrics , 1996, Medical Image Anal..

[47]  Jinah Park,et al.  Deformable models with parameter functions for cardiac motion analysis from tagged MRI data , 1996, IEEE Trans. Medical Imaging.

[48]  T. Lindeberg,et al.  Scale-Space Theory : A Basic Tool for Analysing Structures at Different Scales , 1994 .

[49]  G S Kassab,et al.  Morphometry of pig coronary arterial trees. , 1993, The American journal of physiology.

[50]  James B Bassingthwaighte,et al.  Lightning and the heart: fractal behavior in cardiac function , 1988, Proc. IEEE.