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Artificial Intelligence for Computational Modeling of the Heart

Author: Tommaso Mansi

Publisher: Academic Press

Published: 2019-12

Total Pages: 274

ISBN-13: 012817594X

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Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation

Book Synopsis Artificial Intelligence for Computational Modeling of the Heart by : Tommaso Mansi

Download or read book Artificial Intelligence for Computational Modeling of the Heart written by Tommaso Mansi and published by Academic Press. This book was released on 2019-12 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation

Artificial Intelligence for Computational Modeling of the Heart

Author: Tommaso Mansi

Publisher: Academic Press

Published: 2019-11-25

Total Pages: 274

ISBN-13: 0128168951

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Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient’s heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation

Book Synopsis Artificial Intelligence for Computational Modeling of the Heart by : Tommaso Mansi

Download or read book Artificial Intelligence for Computational Modeling of the Heart written by Tommaso Mansi and published by Academic Press. This book was released on 2019-11-25 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient’s heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation

Artificial Intelligence in Heart Modelling

Author: Rafael Sebastian

Publisher: Frontiers Media SA

Published: 2022-05-11

Total Pages: 356

ISBN-13: 2889761509

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Book Synopsis Artificial Intelligence in Heart Modelling by : Rafael Sebastian

Download or read book Artificial Intelligence in Heart Modelling written by Rafael Sebastian and published by Frontiers Media SA. This book was released on 2022-05-11 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge

Author: Esther Puyol Antón

Publisher: Springer Nature

Published: 2022-01-14

Total Pages: 397

ISBN-13: 3030937224

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This book constitutes the proceedings of the 12th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2021, as well as the M&Ms-2 Challenge: Multi-Disease, Multi-View and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. The 25 regular workshop papers included in this volume were carefully reviewed and selected after being revised. They deal with cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, artificial intelligence, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods. In addition, 15 papers from the M&MS-2 challenge are included in this volume. The Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge (M&Ms-2) is focusing on the development of generalizable deep learning models for the Right Ventricle that can maintain good segmentation accuracy on different centers, pathologies and cardiac MRI views. There was a total of 48 submissions to the workshop.

Book Synopsis Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge by : Esther Puyol Antón

Download or read book Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge written by Esther Puyol Antón and published by Springer Nature. This book was released on 2022-01-14 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 12th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2021, as well as the M&Ms-2 Challenge: Multi-Disease, Multi-View and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. The 25 regular workshop papers included in this volume were carefully reviewed and selected after being revised. They deal with cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, artificial intelligence, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods. In addition, 15 papers from the M&MS-2 challenge are included in this volume. The Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge (M&Ms-2) is focusing on the development of generalizable deep learning models for the Right Ventricle that can maintain good segmentation accuracy on different centers, pathologies and cardiac MRI views. There was a total of 48 submissions to the workshop.

Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges

Author: Esther Puyol Anton

Publisher: Springer Nature

Published: 2021-01-28

Total Pages: 427

ISBN-13: 3030681076

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This book constitutes the proceedings of the 11th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2020, as well as two challenges: M&Ms - The Multi-Centre, Multi-Vendor, Multi-Disease Segmentation Challenge, and EMIDEC - Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI Challenge. The 43 full papers included in this volume were carefully reviewed and selected from 70 submissions. They deal with cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, artificial intelligence, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

Book Synopsis Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges by : Esther Puyol Anton

Download or read book Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges written by Esther Puyol Anton and published by Springer Nature. This book was released on 2021-01-28 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 11th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2020, as well as two challenges: M&Ms - The Multi-Centre, Multi-Vendor, Multi-Disease Segmentation Challenge, and EMIDEC - Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI Challenge. The 43 full papers included in this volume were carefully reviewed and selected from 70 submissions. They deal with cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, artificial intelligence, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

Author: Mihaela Pop

Publisher: Springer

Published: 2019-03-05

Total Pages: 497

ISBN-13: 3030120295

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This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

Book Synopsis Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges by : Mihaela Pop

Download or read book Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges written by Mihaela Pop and published by Springer. This book was released on 2019-03-05 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

Computational Cardiovascular Mechanics

Author: Julius M. Guccione

Publisher: Springer Science & Business Media

Published: 2010-01-08

Total Pages: 335

ISBN-13: 1441907300

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Computational Cardiovascular Mechanics provides a cohesive guide to creating mathematical models for the mechanics of diseased hearts to simulate the effects of current treatments for heart failure. Clearly organized in a two part structure, this volume discusses various areas of computational modeling of cardiovascular mechanics (finite element modeling of ventricular mechanics, fluid dynamics) in addition to a description an analysis of the current applications used (solid FE modeling, CFD). Edited by experts in the field, researchers involved with biomedical and mechanical engineering will find Computational Cardiovascular Mechanics a valuable reference.

Book Synopsis Computational Cardiovascular Mechanics by : Julius M. Guccione

Download or read book Computational Cardiovascular Mechanics written by Julius M. Guccione and published by Springer Science & Business Media. This book was released on 2010-01-08 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Cardiovascular Mechanics provides a cohesive guide to creating mathematical models for the mechanics of diseased hearts to simulate the effects of current treatments for heart failure. Clearly organized in a two part structure, this volume discusses various areas of computational modeling of cardiovascular mechanics (finite element modeling of ventricular mechanics, fluid dynamics) in addition to a description an analysis of the current applications used (solid FE modeling, CFD). Edited by experts in the field, researchers involved with biomedical and mechanical engineering will find Computational Cardiovascular Mechanics a valuable reference.

Machine Learning in Cardiovascular Medicine

Author: Subhi J. Al'Aref

Publisher: Academic Press

Published: 2020-11-20

Total Pages: 456

ISBN-13: 0128202742

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Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Book Synopsis Machine Learning in Cardiovascular Medicine by : Subhi J. Al'Aref

Download or read book Machine Learning in Cardiovascular Medicine written by Subhi J. Al'Aref and published by Academic Press. This book was released on 2020-11-20 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers

Author: Oscar Camara

Publisher: Springer Nature

Published: 2023-01-27

Total Pages: 527

ISBN-13: 303123443X

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This book constitutes the proceedings of the 13th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2022, held in conjunction with the 25th MICCAI conference. The 34 regular workshop papers included in this volume were carefully reviewed and selected after being revised and deal with topics such as: common cardiac segmentation and modelling problems to more advanced generative modelling for ageing hearts, learning cardiac motion using biomechanical networks, physics-informed neural networks for left atrial appendage occlusion, biventricular mechanics for Tetralogy of Fallot, ventricular arrhythmia prediction by using graph convolutional network, and deeper analysis of racial and sex biases from machine learning-based cardiac segmentation. In addition, 14 papers from the CMRxMotion challenge are included in the proceedings which aim to assess the effects of respiratory motion on cardiac MRI (CMR) imaging quality and examine the robustness of segmentation models in face of respiratory motion artefacts. A total of 48 submissions to the workshop was received.

Book Synopsis Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers by : Oscar Camara

Download or read book Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers written by Oscar Camara and published by Springer Nature. This book was released on 2023-01-27 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 13th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2022, held in conjunction with the 25th MICCAI conference. The 34 regular workshop papers included in this volume were carefully reviewed and selected after being revised and deal with topics such as: common cardiac segmentation and modelling problems to more advanced generative modelling for ageing hearts, learning cardiac motion using biomechanical networks, physics-informed neural networks for left atrial appendage occlusion, biventricular mechanics for Tetralogy of Fallot, ventricular arrhythmia prediction by using graph convolutional network, and deeper analysis of racial and sex biases from machine learning-based cardiac segmentation. In addition, 14 papers from the CMRxMotion challenge are included in the proceedings which aim to assess the effects of respiratory motion on cardiac MRI (CMR) imaging quality and examine the robustness of segmentation models in face of respiratory motion artefacts. A total of 48 submissions to the workshop was received.

Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges

Author: Mihaela Pop

Publisher: Springer Nature

Published: 2020-01-22

Total Pages: 426

ISBN-13: 3030390748

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This book constitutes the thoroughly refereed post-workshop proceedings of the 10th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 42 revised full workshop papers were carefully reviewed and selected from 76 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.

Book Synopsis Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges by : Mihaela Pop

Download or read book Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges written by Mihaela Pop and published by Springer Nature. This book was released on 2020-01-22 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 10th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 42 revised full workshop papers were carefully reviewed and selected from 76 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.