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020 _a9783642158353
_9978-3-642-15835-3
040 _cMX-MeUAM
050 4 _aQA75.5-76.95
082 0 4 _a006
_223
100 1 _aCamara, Oscar.
_eeditor.
245 1 0 _aStatistical Atlases and Computational Models of the Heart
_h[recurso electrónico] :
_bFirst International Workshop, STACOM 2010, and Cardiac Electrophysiological Simulation Challenge, CESC 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010. Proceedings /
_cedited by Oscar Camara, Mihaela Pop, Kawal Rhode, Maxime Sermesant, Nic Smith, Alistair Young.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _aXII, 292p. 140 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v6364
505 0 _aKeynote Presentations -- Atlas Construction and Image Analysis Using Statistical Cardiac Models -- Patient-Specific Modeling of the Heart: Applications to Cardiovascular Disease Management -- The Generation of Patient-Specific Heart Models for Diagnosis and Interventions -- Methods and Infrastructure for Atlas Construction -- The Cardiac Atlas Project: Rationale, Design and Procedures -- The Cardiac Atlas Project: Preliminary Description of Heart Shape in Patients with Myocardial Infarction -- The Cardiac Atlas Project: Development of a Framework Integrating Cardiac Images and Models -- Atlas-Based Quantification of Myocardial Motion Abnormalities: Added-value for the Understanding of CRT Outcome? -- Towards High-Resolution Cardiac Atlases: Ventricular Anatomy Descriptors for a Standardized Reference Frame -- Structure and Flow -- Robust Atlas-Based Segmentation of Highly Variable Anatomy: Left Atrium Segmentation -- Atlas-Based Reduced Models of Blood Flows for Fast Patient-Specific Simulations -- Image and Physiological Data Fusion for Guidance and Modelling of Cardiac Resynchronization Therapy Procedures -- A Multi-method Approach towards Understanding the Pathophysiology of Aortic Dissections – The Complementary Role of In-Silico, In-Vitro and In-Vivo Information -- Endowing Canonical Geometries to Cardiac Structures -- Automatic Segmentation of Left Atrial Geometry from Contrast-Enhanced Magnetic Resonance Images Using a Probabilistic Atlas -- Interactive Cardiac Image Analysis for Biventricular Function of the Human Heart -- Cardiac Motion Estimation Using a ProActive Deformable Model: Evaluation and Sensitivity Analysis -- Investigating Heart Failure Using Ventricular Imaging and Modelling -- Incorporating Low-Level Constraints for the Retrieval of Personalised Heart Models from Dynamic MRI -- Volumetric Myocardial Mechanics from 3D+t Ultrasound Data with Multi-model Tracking -- Mechanics and Motion -- Cardiac Active Contraction Parameters Estimated from Magnetic Resonance Imaging -- Electrophysiology and Electrical Activation -- Recovering Cardiac Electrical Activity from Medical Image Sequence: A Model-Based Approach -- Non-invasive Activation Times Estimation Using 3D Echocardiography -- Modeling Drug Effects on Personalized 3D Models of the Heart: A Simulation Study -- How Much Geometrical Detail Do We Need in Cardiac Electrophysiological Imaging? A Generic Heart-Torso Representation for Fast Subject-Specific Customization -- Influence of Geometric Variations on LV Activation Times: A Study on an Atlas-Based Virtual Population -- Computational Electrophysiological Simulation Challenge (CESC 2010) -- Generic Conduction Parameters for Predicting Activation Waves in Customised Cardiac Electrophysiology Models -- A Statistical Physiological-Model-Constrained Framework for Computational Imaging of Subject-Specific Volumetric Cardiac Electrophysiology Using Optical Imaging and MRI Data -- Estimation of Reaction, Diffusion and Restitution Parameters for a 3D Myocardial Model Using Optical Mapping and MRI -- Personalization of Fast Conduction Purkinje System in Eikonal-Based Electrophysiological Models with Optical Mapping Data.
520 _aRecently, there has been considerable progress in the construction and appli- tion of cardiac atlases and computational models which integrate heart shape, function, and physiology. Severalmajorinitiatives haveidenti?ed computational and morphological atlases as a major infrastructural platform, for instance the Physiome project and the European Virtual PhysiologicalHuman project. N- invasive cardiovascular imaging plays an important role in de?ning the com- tational domain, the boundary/initial conditions, and tissue function and pr- erties. Hence, one of the most important current challenges in the ?eld is the development of robust and e?ective methods for the parameterization and p- sonalizationofthesecomputationalmodelsusingonlyminimally-invasiveclinical imaging. However,in orderto evaluatethe model outputandachieveclinical- pact, such personalized models have to be both augmented with and compared to generic knowledge on the healthy and pathological heart. This knowledge can be acquired through the building of statistical models of the heart. Several e?orts are now established to provide web-accessible structural and functional atlases of the normal and pathological heart for clinical, research, and edu- tionalpurposes. Webelievealltheseapproacheswillonlybee?ectivelydeveloped throughcollaborationacrossthe full researchscopeof the imaging andmodeling communities. Integrative models of cardiac function are important for understanding d- ease,evaluating treatment,and planning intervention. To providea focus for the developingarrayoftechniques whichunderpin the applicationofthese models in the clinic a simulation challenge was included in the workshop. The goal of this challenge was to compare strategies for the personaliszation of di?erent cardiac computationalmodelswith experimentaldata. A completedatasetwasprovided in advance, containing the cardiac geometry and ?bre orientations from MRI as well as epicardial transmembrane potentials from optical mapping.
650 0 _aComputer science.
650 0 _aInformation storage and retrieval systems.
650 0 _aMultimedia systems.
650 0 _aElectronic data processing.
650 0 _aComputer vision.
650 0 _aBioinformatics.
650 1 4 _aComputer Science.
650 2 4 _aComputing Methodologies.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aComputational Biology/Bioinformatics.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aUser Interfaces and Human Computer Interaction.
650 2 4 _aMultimedia Information Systems.
700 1 _aPop, Mihaela.
_eeditor.
700 1 _aRhode, Kawal.
_eeditor.
700 1 _aSermesant, Maxime.
_eeditor.
700 1 _aSmith, Nic.
_eeditor.
700 1 _aYoung, Alistair.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642158346
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v6364
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-15835-3
596 _a19
942 _cLIBRO_ELEC
999 _c203027
_d203027