Current-based 4D shape analysis for the mechanical personalization of heart models

Loïc Le Folgoc; Hervé Delingette; Antonio Criminisi; Nicholas Ayache

doi:10.1007/978-3-642-36620-8_28

Current-based 4D shape analysis for the mechanical personalization of heart models

Loïc Le Folgoc
, Hervé Delingette
, Antonio Criminisi
, Nicholas Ayache

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Patient-specific models of the heart may lead to better understanding of cardiovascular diseases and better planning of therapy. A machine-learning approach to the personalization of an electro-mechanical model of the heart, from the kinematics of the endo- and epicardium, is presented in this paper. We use 4D mathematical currents to encapsulate information about the shape and deformation of the heart. The method is largely insensitive to initialization and does not require on-line simulation of the cardiac function. In this work, we demonstrate the performance of our approach for the joint estimation of three parameters on one heart geometry. We manage to retrieve parameters such that the model matches the 4D observations with an accuracy below the voxel size, in less than three minutes of computation.

Original language	English
Title of host publication	Medical Computer Vision
Subtitle of host publication	Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers
Pages	283-292
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-36620-8_28
Publication status	Published - 25 Mar 2013
Externally published	Yes
Event	2nd MICCAI Workshop on Medical Computer Vision, MICCAI-MCV 2012, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 - Nice, France Duration: 5 Oct 2012 → 5 Oct 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7766 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd MICCAI Workshop on Medical Computer Vision, MICCAI-MCV 2012, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
Country/Territory	France
City	Nice
Period	5/10/12 → 5/10/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

currents
machine-learning
mechanical personalization
patient-specific heart model

Access to Document

10.1007/978-3-642-36620-8_28

Cite this

Le Folgoc, L., Delingette, H., Criminisi, A., & Ayache, N. (2013). Current-based 4D shape analysis for the mechanical personalization of heart models. In Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers (pp. 283-292). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7766 LNCS). https://doi.org/10.1007/978-3-642-36620-8_28

Le Folgoc, Loïc ; Delingette, Hervé ; Criminisi, Antonio et al. / Current-based 4D shape analysis for the mechanical personalization of heart models. Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers. 2013. pp. 283-292 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Current-based 4D shape analysis for the mechanical personalization of heart models",

abstract = "Patient-specific models of the heart may lead to better understanding of cardiovascular diseases and better planning of therapy. A machine-learning approach to the personalization of an electro-mechanical model of the heart, from the kinematics of the endo- and epicardium, is presented in this paper. We use 4D mathematical currents to encapsulate information about the shape and deformation of the heart. The method is largely insensitive to initialization and does not require on-line simulation of the cardiac function. In this work, we demonstrate the performance of our approach for the joint estimation of three parameters on one heart geometry. We manage to retrieve parameters such that the model matches the 4D observations with an accuracy below the voxel size, in less than three minutes of computation.",

keywords = "currents, machine-learning, mechanical personalization, patient-specific heart model",

author = "\{Le Folgoc\}, Lo{\"i}c and Herv{\'e} Delingette and Antonio Criminisi and Nicholas Ayache",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Medical Computer Vision",

note = "2nd MICCAI Workshop on Medical Computer Vision, MICCAI-MCV 2012, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 ; Conference date: 05-10-2012 Through 05-10-2012",

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Le Folgoc, L, Delingette, H, Criminisi, A & Ayache, N 2013, Current-based 4D shape analysis for the mechanical personalization of heart models. in Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7766 LNCS, pp. 283-292, 2nd MICCAI Workshop on Medical Computer Vision, MICCAI-MCV 2012, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, Nice, France, 5/10/12. https://doi.org/10.1007/978-3-642-36620-8_28

Current-based 4D shape analysis for the mechanical personalization of heart models. / Le Folgoc, Loïc; Delingette, Hervé; Criminisi, Antonio et al.
Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers. 2013. p. 283-292 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7766 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Current-based 4D shape analysis for the mechanical personalization of heart models

AU - Le Folgoc, Loïc

AU - Delingette, Hervé

AU - Criminisi, Antonio

AU - Ayache, Nicholas

PY - 2013/3/25

Y1 - 2013/3/25

N2 - Patient-specific models of the heart may lead to better understanding of cardiovascular diseases and better planning of therapy. A machine-learning approach to the personalization of an electro-mechanical model of the heart, from the kinematics of the endo- and epicardium, is presented in this paper. We use 4D mathematical currents to encapsulate information about the shape and deformation of the heart. The method is largely insensitive to initialization and does not require on-line simulation of the cardiac function. In this work, we demonstrate the performance of our approach for the joint estimation of three parameters on one heart geometry. We manage to retrieve parameters such that the model matches the 4D observations with an accuracy below the voxel size, in less than three minutes of computation.

AB - Patient-specific models of the heart may lead to better understanding of cardiovascular diseases and better planning of therapy. A machine-learning approach to the personalization of an electro-mechanical model of the heart, from the kinematics of the endo- and epicardium, is presented in this paper. We use 4D mathematical currents to encapsulate information about the shape and deformation of the heart. The method is largely insensitive to initialization and does not require on-line simulation of the cardiac function. In this work, we demonstrate the performance of our approach for the joint estimation of three parameters on one heart geometry. We manage to retrieve parameters such that the model matches the 4D observations with an accuracy below the voxel size, in less than three minutes of computation.

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BT - Medical Computer Vision

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Le Folgoc L, Delingette H, Criminisi A, Ayache N. Current-based 4D shape analysis for the mechanical personalization of heart models. In Medical Computer Vision: Recognition Techniques and Applications in Medical Imaging - Second International MICCAI Workshop, MCV 2012, Revised Selected Papers. 2013. p. 283-292. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-36620-8_28

Current-based 4D shape analysis for the mechanical personalization of heart models

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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