Artificial Intelligence For Computational Modeling Of The Heart
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Artificial Intelligence for Computational Modeling of the Heart
Author | : Tommaso Mansi,Tiziano Passerini,Dorin Comaniciu |
Publsiher | : Academic Press |
Total Pages | : 274 |
Release | : 2019-12 |
Genre | : Science |
ISBN | : 9780128175941 |
Download Artificial Intelligence for Computational Modeling of the Heart Book in PDF, Epub and Kindle
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,Tiziano Passerini,Dorin Comaniciu |
Publsiher | : Academic Press |
Total Pages | : 274 |
Release | : 2019-11-25 |
Genre | : Science |
ISBN | : 9780128168950 |
Download Artificial Intelligence for Computational Modeling of the Heart Book in PDF, Epub and Kindle
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,Linwei Wang,Natalia A. Trayanova |
Publsiher | : Frontiers Media SA |
Total Pages | : 356 |
Release | : 2022-05-11 |
Genre | : Science |
ISBN | : 9782889761500 |
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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,Mihaela Pop,Carlos Martín-Isla,Maxime Sermesant,Avan Suinesiaputra,Oscar Camara,Karim Lekadir,Alistair Young |
Publsiher | : Springer Nature |
Total Pages | : 397 |
Release | : 2022-01-14 |
Genre | : Computers |
ISBN | : 9783030937225 |
Download Statistical Atlases and Computational Models of the Heart Multi Disease Multi View and Multi Center Right Ventricular Segmentation in Cardiac MRI Challenge Book in PDF, Epub and Kindle
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,Mihaela Pop,Maxime Sermesant,Victor Campello,Alain Lalande,Karim Lekadir,Avan Suinesiaputra,Oscar Camara,Alistair Young |
Publsiher | : Springer Nature |
Total Pages | : 427 |
Release | : 2021-01-28 |
Genre | : Computers |
ISBN | : 9783030681074 |
Download Statistical Atlases and Computational Models of the Heart M Ms and EMIDEC Challenges Book in PDF, Epub and Kindle
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,Maxime Sermesant,Jichao Zhao,Shuo Li,Kristin McLeod,Alistair Young,Kawal Rhode,Tommaso Mansi |
Publsiher | : Springer |
Total Pages | : 497 |
Release | : 2019-03-05 |
Genre | : Computers |
ISBN | : 9783030120290 |
Download Statistical Atlases and Computational Models of the Heart Atrial Segmentation and LV Quantification Challenges Book in PDF, Epub and Kindle
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,Ghassan Kassab,Mark B. Ratcliffe |
Publsiher | : Springer Science & Business Media |
Total Pages | : 335 |
Release | : 2010-01-08 |
Genre | : Technology & Engineering |
ISBN | : 9781441907301 |
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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.
Statistical Atlases and Computational Models of the Heart Multi Sequence CMR Segmentation CRT EPiggy and LV Full Quantification Challenges
Author | : Mihaela Pop,Maxime Sermesant,Oscar Camara,Xiahai Zhuang,Shuo Li,Alistair Young,Tommaso Mansi,Avan Suinesiaputra |
Publsiher | : Springer Nature |
Total Pages | : 426 |
Release | : 2020-01-22 |
Genre | : Computers |
ISBN | : 9783030390747 |
Download Statistical Atlases and Computational Models of the Heart Multi Sequence CMR Segmentation CRT EPiggy and LV Full Quantification Challenges Book in PDF, Epub and Kindle
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.