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Multi-modality platform for specific imaging in cardiology



MUSIC (Multi-modality Platform for Specific Imaging in Cardiology) is a proprietary software developed by the Liryc IHU and the Epione Inria team, and based on medInria open-source software. The aim is to offer a large spectrum of functionalities and processing pipelines dedicated to cardiology. 


Tools and multi-modality: segmentation, visualization, filters, histograms, data reformating, registration and mesh processing tools are provided in MUSIC and allow the community to use a user-friendly common framework for more efficiency. Many imaging modalities are supported: MDCT (scanner), MRI, PET, VTK meshes. In addition, the models generated by MUSIC can be exported to clinical 3D electroanatomical mapping systems used by cardiologists during procedures on electrical disorders (ablation by catheter).


Treatment improvement: MUSIC offers imaging algorithms for diagnosis and prognosis, pipelines dedicated to the guidance of atrial or ventricular interventions through imaging. Thus, MUSIC has been used to guide scar-related ventricular tachycardia (VT) ablation in over 300 consecutive procedures in our center, and more than 1.500 in the international MUSIC network. In addition, this multicentral network allows to built an international registry of structural cardiac pathologies including imagery and electro-physiology data.


View the presentation of Music:






A bonus for Research: MUSIC is a software platform allowing the analysis, in one environment, of multi-parametric data sets from the IHU teams (structural, mechanic, hemodynamic, electrical, etc), and to interface with simulation platforms such as SOFA, CEPS, CARP in order to develop patient-specific modelisation/simulation strategies.


Consortium: an international consortium of experienced VT centers has been built as part of the MUSIC program. It now regroups more than 30 international centers. Participating centers upload their anonymised data to our team on a web-portal. Our operators process the data in a few hours and send the results to the centers in time for the intervention. Thus, cardiologists all around the world use this technology every day to guide their procedures and visualize their catheters in real-time inside a virtual patient-specific heart created in Bordeaux.


Our team: the MUSIC project has been pursued by a multidisciplinary team involving doctors, researchers, software developers, and medical imaging operators.


Project contributors :
Tech Leads:

  •     Florent Collot (Developer)
  •     Mathilde Merle (Developer)


  •     Loic Cadour (Developer)
  •     Julien Castelneau (Developer)
  •     Nordine El Baraka (Developer)
  •     Mehdi Juhoor (Developer)
  •     Pauline Migerditichan (Developer)
  •     Florian Vichot (Developer)

Doctoral student:

  •     Jatin Relan (Doctoral student)

Scientific Coordinator:

  •     Maxime Sermesant (Researcher)

Clinical Coordinators:    

  •     Hubert Cochet (Radiologist): Cardiac image analysis
  •     Pierre Jais (Cardiologist): guiding interventions

Data Analysis:

  •     Olivier Baris (Radio Manipulator)
  •     Ludovic Germain (Radio manipulator)
  •     Bruno Soré (Radio manipulator)
  •     Jean Michel Thomas (Radio manipulator)

Imaging team leader:

  •     Bruno Quesson (Researcher)

"Signal processing" team leader :

  •     Rémi Dubois (Researcher)

Modeling team, "Carmen" Inria team:

  •     Nejib Zemzemi (Researcher)
  •     Yves Coudiere (Researcher)


To contact us : here


This work has benefited from:

  •     State grant managed by the National Research Agency under the program "Investments in the future" bearing the reference "ANR-11-EQPX-0030".
  •     IDAM: engineering for the integration of cardiac electrophysiology images, data and models. 2015/2017
  •     EPICARD-VIZ : electrocardiographic imaging tool: simulation and visualization. 2016/2018
  •     CIESCARD: combining electrical and structural information to help cardiologists better target cardiac therapy. 2018/2020
  •     ECSTATIC:


To find out more : Report "The rhythm of the heart" (video)


Publications : 



  1. A Spatial Adaptation of the Time Delay Neural Network for Solving ECGI Inverse Problem. Amel Karoui, Mostafa Bendahmane, Nejib Zemzemi, Yves Coudière; Valéry Ozenne; Edward Vigmond; Nejib Zemzemi. 10th International Symposium Functional Imaging and Modeling of the Heart, 11504, Springer, pp.94-102, 2019, Lecture Notes in Computer Science, 978-3-030-21949-9. ⟨10.1007/978-3-030-21949-9_11⟩
  2. Berte et al.Image-guided ablation of scar-related ventricular tachycardia: towards a shorter and more predictable procedure. Journal of Interventional Cardiac Electrophysiology - 2019 Dec.
  3. Direct Mapping from Body Surface Potentials to Cardiac Activation Maps Using Neural NetworksAmel Karoui, Mostafa Bendahmane, Nejib Zemzemi. CinC 2019 – 46th Computing in Cardiology Conference, Sep 2019,Singapour, Singapore
  4. Space rescaling in the MFS method improves the ECGI reconstruction. Pauline Migerditichan, Mark Potse, Nejib Zemzemi. CinC 2019 – Computing in Cardiology 2019, Sep 2019, Singapour, Singapore
  5. Takigawa et al. Are wall thickness channels defined by computed tomography predictive of isthmuses of post-infarction ventricular tachycardia? Heart Rhythm – 2019 Jun;14 pii: S1547-5271(19)30557-0. 
  6. Takigawa et al.Detailed comparison between the wall thickness and voltages in chronic myocardial infarction. Journal of Cardiovascular Electrophysiology – 2019 Feb;30(2):195-204
  7. Cabrera Lozoya et al.Model-Based Feature Augmentation for Cardiac Ablation Target Learning From Images. IEEE Transactions in Biomedical Engineering – 2019 Jan;66(1):30-40. 



  1. Evaluation of fifteen algorithms for the resolution of the electrocardiography imaging inverse problem using ex-vivo and in-silico data. Amel Karoui, Laura Bear, Pauline Migerditichan, Nejib Zemzemi. Frontiers in Physiology, Frontiers, 2018, Electrocardiographic Imaging, 9, pp.1708
  2. Cedilnik et al.Fast personalised electrophysiological models from CT images for VT ablation planning. EP EUROPACE – 2018 2018 Nov 1;20(suppl_3):iii94-iii101. 
  3. The Heart Recording Conditions Impact the Assessment of the Electrocardiography Imaging Inverse Solution. Amel Karoui, Laura Bear, Pauline Migerditichan, Mostafa Bendahmane, Nejib Zemzemi.CinC 2018 – 45th Computing in Cardiology Conference, Sep 2018, Maastricht, Netherlands
  4. Teijeira‐Fernandez et al.Influence of contact force on voltage mapping: A combined magnetic resonance imaging and electroanatomic mapping study in patients with tetralogy of fallotHeart Rhythm – 2018 Aug;15(8):1198-1205. 
  5. Ghannam et al.Correlation between computer tomography‐derived scar topography and critical ablation sites in postinfarction ventricular tachycardia. Journal of Cardiovascular Electrophysiology – 2018 Mar;29(3):438‐445. 
  6. Wolf et al.Long-term outcome of substrate modification in ablation of post-myocardial infarction ventricular tachycardia Circulation: Arrhythmia and Electrophysiology – 2018 Feb;11(2):e005635.
  7. Cochet et al.Relationship between fibrosis detected on late gadolinium-enhanced cardiac magnetic resonance and re-entrant activity assessed with electrocardiographic imaging in human persistent atrial fibrillation. JACC: Clinical Electrophysiology – 2018 Jan;4(1):17-29. 


  1. Mahida et al.Cardiac imaging in patients with ventricular tachycardia. Circulation – 2017 Dec 19;136(25):2491-2507. 
  2. Pierre Jaïs.CT scan isthmuses as an imaging target for VT ablation. International Symposium on Ventricular Arrhythmias – 2017. 
  3. Cedilnik et al.VT scan: Towards an efficient pipeline from computed tomography images to ventricular tachycardia ablation. Functional Imaging and Modelling of the Heart (FIMH) – 2017, Lecture Notes in Computer Science, vol 10263. 
  4. Cabrera-Lozoya R, et al. Image-Based Biophysical Simulation of Intracardiac Abnormal Ventricular Electrograms. IEEE Trans Biomed Eng. 2017 Jul;64(7):1446-1454.
  5. Thompson et al..Catheter ablation for ventricular tachycardia in patients with nonischemic cardiomyopathy. Cardiac Electrophysiology Clinics – 2017 Mar;9(1):47-54. 
  6. Yamashita S, et al. Myocardial wall thinning predicts transmural substrate in patients with scar-related ventricular tachycardia. Heart Rhythm. 2017 Feb;14(2):155-163.



  1. Roney CH, et al. Modelling methodology of atrial fibrosis affects rotor dynamics and electrograms. Europace. 2016 Dec;18(suppl 4):iv146-iv155.
  2. Yamashita S, et alImpact of New Technologies and Approaches for Post-Myocardial Infarction Ventricular Tachycardia Ablation During Long-Term Follow-Up. Circ Arrhythm Electrophysiol. 2016 Jul;9(7).
  3. Zahid S, et alPatient-derived models link re-entrant driver localization in atrial fibrillation to fibrosis spatial pattern. Cardiovasc Res. 2016 Jun 1;110(3):443-54.
  4. Vigmond E, et al. Percolation as a mechanism to explain atrial fractionated electrograms and reentry in a fibrosis model based on imaging data. Heart Rhythm. 2016 Jul;13(7):1536-43.
  5. Yamashita S, et al. Image Integration to Guide Catheter Ablation in Scar-Related Ventricular Tachycardia. J Cardiovasc Electrophysiol. 2016 Jun;27(6):699-708.
  6. Haissaguerre M, et alIntermittent drivers anchoring to structural heterogeneities as a major pathophysiological mechanism of human persistent atrial fibrillation. J Physiol. 2016 May 1;594(9):2387-98.



  1. Berte B, et alIrrigated Needle Ablation Creates Larger and More Transmural Ventricular Lesions Compared With Standard Unipolar Ablation in an Ovine Model. Circ Arrhythm Electrophysiol. 2015 Dec;8(6):1498-506.
  2. Berte B, et alCharacterization of the Left-Sided Substrate in Arrhythmogenic Right Ventricular Cardiomyopathy. Circ Arrhythm Electrophysiol. 2015 Aug 26. pii: CIRCEP.115.003213. [Epub ahead of print]
  3. Berte B, et alEpicardial only mapping and ablation of ventricular tachycardia: a case series. Europace. 2015 Apr 2. pii: euv072. [Epub ahead of print]
  4. Cochet H, Mouries A, Nivet H, Sacher F, Derval N, Denis A, Merle M, Relan J, Hocini M, Haïssaguerre M, Laurent F, Montaudon M, Jaïs P. Age, atrial fibrillation, and structural heart disease are the main determinants of left atrial fibrosis detected by delayed-enhanced magnetic resonance imaging in a general cardiology population. J Cardiovasc Electrophysiol. 2015 May;26(5):484-92.
  5. Yamashita S, et alRole of high-resolution image integration to visualize left phrenic nerve and coronary arteries during epicardial ventricular tachycardia ablation. Circ Arrhythm Electrophysiol. 2015 Apr;8(2):371-80.
  6. Cochet H, et alAutomated Quantification of Right Ventricular Fat at Contrast-enhanced Cardiac Multidetector CT in Arrhythmogenic Right Ventricular Cardiomyopathy. Radiology. 2015 Jan 5:141140. [Epub ahead of print]
  7. Berte B, et alPostmyocarditis ventricular tachycardia in patients with epicardial-only scar: a specific entity requiring a specific approach. J Cardiovasc Electrophysiol. 2015 Jan;26(1):42-50.



  1. Labarthe S, et alA bilayer model of human atria: mathematical background, construction, and assessment. Europace. 2014 Nov;16 Suppl 4:iv21-iv29.
  2. Komatsu Y, et alRelationship between MDCT-imaged myocardial fat and ventricular tachycardia substrate in arrhythmogenic right ventricular cardiomyopathy. J Am Heart Assoc. 2014 Aug 7;3(4).
  3. Cochet H, et alAtrial structure and function 5 years after successful ablation for persistent atrial fibrillation: an MRI study. J Cardiovasc Electrophysiol. 2014 Jul;25(7):671-9.
  4. Cochet H, et alCardiac arrythmias: multimodal assessment integrating body surface ECG mapping into cardiac imaging. Radiology. 2014 Apr;271(1):239-47.



  1. Vigmond E, et alA bilayer representation of the human atria. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:1530-3.
  2. Komatsu Y, et alMultimodality imaging to improve the safety and efficacy of epicardial ablation of scar-related ventricular tachycardia. J Cardiovasc Electrophysiol. 2013 Dec;24(12):1426-7.
  3. Jadidi AS, et al. Inverse relationship between fractionated electrograms and atrial fibrosis in persistent atrial fibrillation: combined magnetic resonance imaging and high-density mapping. J Am Coll Cardiol 2013;62:802-12.
  4. Komatsu Y, et alRegional myocardial wall thinning at multidetector computed tomography correlates to arrhythmogenic substrate in postinfarction ventricular tachycardia: assessment of structural and electrical substrate. Circ Arrhythm Electrophysiol 2013;6:342-50.
  5. Hocini M, et alNoninvasive electrocardiomapping facilitates previously failed ablation of right appendage diverticulum associated life-threatening accessory pathway. J Cardiovasc Electrophysiol 2013;24:583-5.
  6. Cochet H, et alIntegration of merged delayed-enhanced magnetic resonance Imaging and multidetector computed tomography for the guidance of ventricular tachycardia ablation: a pilot study. J Cardiovasc Electrophysiol 2013;24:419-26.