A. Prakosa

发表

Benchmarking framework for myocardial tracking and deformation algorithms: An open access database

Alejandro F. Frangi, Kawal S. Rhode, Daniel Rueckert, 2013, Medical Image Anal..

An Incompressible Log-Domain Demons Algorithm for Tracking Heart Tissue

Maxime Sermesant, Xavier Pennec, Tommaso Mansi, 2011, STACOM.

Personalized virtual-heart technology for guiding the ablation of infarct-related ventricular tachycardia

Joshua J. E. Blauer, Frederick T. Han, H. Halperin, 2018, Nature Biomedical Engineering.

Computationally guided personalized targeted ablation of persistent atrial fibrillation

Stefan L. Zimmerman, Rheeda L. Ali, David D Spragg, 2019, Nature Biomedical Engineering.

Computational Identification of Ventricular Arrhythmia Risk in Pediatric Myocarditis

N. Trayanova, A. Prakosa, P. Nikolov, 2019, Pediatric Cardiology.

Sensitivity of Ablation Targets Prediction to Electrophysiological Parameter Variability in Image-Based Computational Models of Ventricular Tachycardia in Post-infarction Patients

N. Trayanova, A. Prakosa, P. Nikolov, 2019, Front. Physiol..

Accurate Conduction Velocity Maps and Their Association With Scar Distribution on Magnetic Resonance Imaging in Patients With Postinfarction Ventricular Tachycardias

Rheeda L. Ali, N. Trayanova, H. Ashikaga, 2020, Circulation. Arrhythmia and electrophysiology.

Characterizing Conduction Channels in Postinfarction Patients Using a Personalized Virtual Heart.

N. Trayanova, A. Prakosa, P. Nikolov, 2019, Biophysical journal.

Feasibility study shows concordance between image‐based virtual‐heart ablation targets and predicted ECG‐based arrhythmia exit‐sites

N. Trayanova, A. Prakosa, K. Aronis, 2021, Pacing and clinical electrophysiology : PACE.

Analysis and simulation of multimodal cardiac images to study the heart function

A. Prakosa, 2013 .

New Results - Medical Image Analysis

Hervé Delingette, Olivier Clatz, Ezequiel Geremia, 2009 .

Lack of regional association between atrial late gadolinium enhancement on cardiac magnetic resonance and atrial fibrillation rotors.

Stefan L. Zimmerman, N. Trayanova, H. Calkins, 2016, Heart rhythm.

How personalized heart modeling can help treatment of lethal arrhythmias: A focus on ventricular tachycardia ablation strategies in post‐infarction patients

N. Trayanova, A. Prakosa, A. Doshi, 2020, Wiley interdisciplinary reviews. Systems biology and medicine.

The Fibrotic Substrate in Persistent Atrial Fibrillation Patients: Comparison Between Predictions From Computational Modeling and Measurements From Focal Impulse and Rotor Mapping

N. Trayanova, H. Calkins, H. Ashikaga, 2018, Front. Physiol..

Characterization of Helicobacter pylori tlyA and Its Association with Bacterial Density

A. Prakosa, A. Syam, T. Uchida, 2021, Digestive Diseases.

Spatial dispersion analysis of LGE‐CMR for prediction of ventricular arrhythmias in patients with cardiac sarcoidosis

Katherine C. Wu, N. Trayanova, D. Okada, 2021, Pacing and clinical electrophysiology : PACE.

Arrhythmia in hypertrophic cardiomyopathy: Risk prediction using contrast enhanced MRI, T1 mapping, and personalized virtual heart technology.

N. Trayanova, A. Prakosa, E. Binka, 2022, Journal of electrocardiology.

Fat infiltration in the infarcted heart as a paradigm for ventricular arrhythmias

N. Trayanova, R. Berger, A. Prakosa, 2022, Nature Cardiovascular Research.

Wavefront directionality and decremental stimuli synergistically improve identification of ventricular tachycardia substrate: insights from personalized computational heart models

N. Trayanova, R. Berger, A. Prakosa, 2022, 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.

Abstract 20903: A Novel Approach to Arrhythmia Risk Stratification in Patients With Non-ischemic Cardiomyopathy

Katherine C. Wu, N. Trayanova, A. Prakosa, 2016 .

Abstract 16247: Personalized MRI-Based Modeling Predicts Ventricular Tachycardia Vulnerability in Patients Receiving Primary Prevention ICDs

Joshua J. E. Blauer, Frederick T. Han, N. Trayanova, 2016 .

Computational Re-Entry Vulnerability Index Mapping to Guide Ablation in Patients With Post-Myocardial Infarction Ventricular Tachycardia.

N. Trayanova, A. Prakosa, T. Oostendorp, 2022, JACC. Clinical electrophysiology.

Field of view of mapping catheters quantified by electrogram associations with radius of myocardial attenuation on contrast-enhanced cardiac computed tomography.

Vadim Zipunnikov, Stefan L. Zimmerman, Hugh Calkins, 2018, Heart rhythm.

Image-based reconstruction of three-dimensional myocardial infarct geometry for patient-specific modeling of cardiac electrophysiology.

Eranga Ukwatta, Martin Rajchl, Natalia A Trayanova, 2015, Medical physics.

Substrate Spatial Complexity Analysis for the Prediction of Ventricular Arrhythmias in Patients With Ischemic Cardiomyopathy

Katherine C. Wu, N. Trayanova, M. Maggioni, 2020, Circulation. Arrhythmia and electrophysiology.

Predicting risk of sudden cardiac death in patients with cardiac sarcoidosis using multimodality imaging and personalized heart modeling in a multivariable classifier

N. Trayanova, D. Okada, A. Prakosa, 2021, Science Advances.

Cardiac Electrophysiological Activation Pattern Estimation From Images Using a Patient-Specific Database of Synthetic Image Sequences

Hervé Delingette, Kawal S. Rhode, Nicholas Ayache, 2014, IEEE Transactions on Biomedical Engineering.

Personalized computational heart models with T1-mapped fibrotic remodeling predict sudden death risk in patients with hypertrophic cardiomyopathy

Stefan L. Zimmerman, N. Trayanova, A. Prakosa, 2021, medRxiv.

Methodology for image-based reconstruction of ventricular geometry for patient-specific modeling of cardiac electrophysiology.

A Prakosa, P Malamas, S Zhang, 2014, Progress in biophysics and molecular biology.

Electromechanical modeling of human ventricles with ischemic cardiomyopathy: numerical simulations in sinus rhythm and under arrhythmia

Alfio Quarteroni, Jonathan Chrispin, Luca Dede', 2021, Comput. Biol. Medicine.

Ventricular Arrhythmia Risk Prediction in Repaired Tetralogy of Fallot using Personalized Computational Cardiac Models.

N. Trayanova, A. Prakosa, P. Nikolov, 2020, Heart rhythm.

Generation of Synthetic but Visually Realistic Time Series of Cardiac Images Combining a Biophysical Model and Clinical Images

Hervé Delingette, Nicholas Ayache, Maxime Sermesant, 2013, IEEE Transactions on Medical Imaging.

Novel Helicobacter pylori-associated hemolysis Hp0499 and Hp1490 and its association with severity of gastritis

A. Prakosa, M. Miftahussurur, Titong Sugihartono, 2023, F1000Research.

Feasibility of using patient-specific models and the "minimum cut" algorithm to predict optimal ablation targets for left atrial flutter.

Natalia A Trayanova, Hugh Calkins, Jonathan Chrispin, 2016, Heart rhythm.

The role of structural vs cellular remodeling in arrhythmogenesis: personalized computer models of atrial fibrillation

Andrey V. Pikunov, Rheeda L. Ali, N. Trayanova, 2023, bioRxiv.

Personalized Digital-Heart Technology for Ventricular Tachycardia Ablation Targeting in Hearts With Infiltrating Adiposity

Stefan L. Zimmerman, N. Trayanova, R. Berger, 2020, Circulation: Arrhythmia and Electrophysiology.

A feasibility study of arrhythmia risk prediction in patients with myocardial infarction and preserved ejection fraction.

Natalia A Trayanova, Dongdong Deng, Adityo Prakosa, 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.

3D Strain Assessment in Ultrasound (Straus): A Synthetic Comparison of Five Tracking Methodologies

A. Hennemuth, M. De Craene, S. Marchesseau, 2013, IEEE Transactions on Medical Imaging.

Predicting Ventricular Tachycardia Circuits in Patients with Arrhythmogenic Right Ventricular Cardiomyopathy using Genotype-specific Heart Digital Twins

Stefan L. Zimmerman, N. Trayanova, H. Calkins, 2023, medRxiv.

Analyzing the Role of Repolarization Gradients in Post-infarct Ventricular Tachycardia Dynamics Using Patient-Specific Computational Heart Models

N. Trayanova, A. Prakosa, E. Sung, 2021, Frontiers in Physiology.

Accuracy of prediction of infarct-related arrhythmic circuits from image-based models reconstructed from low and high resolution MRI

Henry Halperin, Hiroshi Ashikaga, Dongdong Deng, 2015, Front. Physiol..

Impact of augmented-reality improvement in ablation catheter navigation as assessed by virtual-heart simulations of ventricular tachycardia ablation

Natalia A. Trayanova, Michael K. Southworth, Adityo Prakosa, 2021, Comput. Biol. Medicine.

Computational and Physical Phantom Setups for the Second Cardiac Motion Analysis Challenge (cMAC2)

Hervé Delingette, Mathieu De Craene, Maxime Sermesant, 2012, STACOM.

Synthetic Echocardiographic Image Sequences for Cardiac Inverse Electro-Kinematic Learning

Hervé Delingette, Nicholas Ayache, Maxime Sermesant, 2011, MICCAI.

Non-invasive Activation Times Estimation Using 3D Echocardiography

Hervé Delingette, Nicholas Ayache, Maxime Sermesant, 2010, STACOM/CESC.

Validity and Reliability of Health-related Quality of Life of Post-stroke Patients

A. Prakosa, Sari Luthfiyah, B. Utomo, 2022, Open Access Macedonian Journal of Medical Sciences.

Predicting ventricular tachycardia circuits in patients with arrhythmogenic right ventricular cardiomyopathy using genotype-specific heart digital twins

A. Prakosa, C. James, C. Tichnell, 2023, eLife.

Up Digital and Personal: How Heart Digital Twins Can Transform Heart Patient Care.

A. Prakosa, Natalia A. Trayanova, 2023, Heart rhythm.

3D Strain Assessment in Ultrasound (Straus): A Synthetic Comparison of Five Tracking Methodologies

A. R. Porras, H. Delingette, Maxime Sermesant, 2013, IEEE Transactions on Medical Imaging.

Methodology for image-based reconstruction of ventricular geometry for patient-specific modeling of cardiac electrophysiology.

D. Herzka, A. Prakosa, A. Lardo, 2014, Progress in biophysics and molecular biology.

Repolarization Gradients Alter Post-infarct Ventricular Tachycardia Dynamics in Patient-Specific Computational Heart Models

Natalia A. Trayanova, Adityo Prakosa, Eric Sung, 2021, 2021 Computing in Cardiology (CinC).

Cardiac MRI Oversampling in Heart Digital Twins Improves Preprocedure Ventricular Tachycardia Identification in Postinfarction Patients.

A. Prakosa, Ryan P O'Hara, Audrey Lacy, 2024, JACC. Clinical electrophysiology.