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| Titel: | Artificial Intelligence in Cardiothoracic Imaging |
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| Mitwirkende: | De Cecco, Carlo N. [HerausgeberIn]  |
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| | van Assen, Marly [HerausgeberIn] |
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| | Leiner, Tim [HerausgeberIn] |
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| Verf.angabe: | edited by Carlo N. De Cecco, Marly van Assen, Tim Leiner |
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| Ausgabe: | 1st ed. 2022. |
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| Verlagsort: | Cham |
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| | Cham |
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| Verlag: | Springer International Publishing |
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| | Imprint: Humana |
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| E-Jahr: | 2022 |
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| Jahr: | 2022. |
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| | 2022. |
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| Umfang: | 1 Online-Ressource(XXIV, 595 p. 233 illus., 200 illus. in color.) |
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| Gesamttitel/Reihe: | Contemporary Medical Imaging |
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| | Springer eBook Collection |
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| ISBN: | 978-3-030-92087-6 |
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| Abstract: | PART I: Artificial Intelligence: Technical Considerations and Fundamentals -- Artificial Intelligence: A Century-Old Story -- Demystifying Artificial Intelligence Technology in Cardiothoracic Imaging: The Essentials -- Artificial Intelligence Algorithm Development for Biomedical Imaging -- Data Preparation for Artificial Intelligence -- Data Storage, Cloud Usage and Artificial Intelligence Pipeline -- How to Build Artificial Intelligence Algorithms for Imaging Applications -- Radiomics: Technical Background -- Biobanks and Artificial Intelligence -- Biostatistics and Artificial Intelligence -- PART II: Artificial Intelligence: General Approaches and Applications -- Structured Reporting in Medical Imaging: the Role of Artificial Intelligence -- Artificial Intelligence: Clinical Relevance and Workflow -- Patient Selection and Scan Preparation Optimization: the Role of Artificial Intelligence -- Artificial Intelligence for Image Enhancement and Reconstruction in Magnetic Resonance Imaging -- Artificial Intelligence Based Image Reconstruction in Cardiac Magnetic Resonance -- Artificial Intelligence Based Image Reconstruction in Computed Tomography Imaging -- Artificial Intelligence Based Contrast Medium Optimization -- Radiation Dose Optimization: the Role of Artificial Intelligence -- Artificial Intelligence Integration into the Computed Tomography System -- Artificial Intelligence Integration into the Magnetic Resonance System -- Magnetic Resonance Fingerprinting: the Role of Artificial Intelligence -- Currently Available Artificial Intelligence Software for Cardiothoracic Imaging -- PART III: Artificial Intelligence: Cardiac Applications -- Cardiac CT Guidelines and Clinical Applications: Where does Artificial Intelligence fit in? -- Natural Language Processing for Cardiovascular Applications -- Artificial Intelligence Based Evaluation of Coronary Calcium -- Artificial Intelligence Based Evaluation of Coronary Atherosclerotic Plaques -- Artificial Intelligence Based Coronary Artery Disease Reporting & Data System (CAD-RADS) -- Artificial Intelligence Based CT Derived Fractional Flow Reserve (CT-FFR) -- Artificial Intelligence Based Evaluation of Cardiac Valves -- Artificial Intelligence Based Diagnosis and Procedural Planning for Aortic Valve Disease -- Artificial Intelligence Based Quantification of Cardiac Fat -- Radiomics in Cardiac CT -- Cardiac MR Guidelines and Clinical Applications: Where does Artificial Intelligence fit in? -- Artificial Intelligence Based Evaluation of Functional Cardiac Magnetic Resonance Imaging -- Magnetic Resonance Imaging based 4D Cardiac Flow: the Role of Artificial Intelligence -- Magnetic Resonance Imaging based Coronary Flow: the Role of Artificial Intelligence -- Artificial Intelligence Based Evaluation of Cardiac Congenital Disease -- Cardiac Nuclear Medicine: the Role of Artificial Intelligence -- Cardiac Ultrasound Imaging: the Role of Artificial Intelligence -- Artificial Intelligence Based Cardiovascular Risk Stratification -- PART IV: Artificial Intelligence: Thoracic Applications -- Artificial Intelligence Based Evaluation of Patients with Chronic Obstructive Pulmonary Disease -- Artificial Intelligence Based Evaluation of Patients with Interstitial Lung Disease -- Artificial Intelligence Based Evaluation of Infectious Disease Imaging: A COVID-19 Perspective -- Artificial Intelligence for Lung Cancer Screening and Nodule Detection -- Artificial Intelligence for Lung Cancer Characterization and Prognosis -- Artificial Intelligence for Opportunistic Chest CT Screening and Prognostication -- Artificial Intelligence Based Detection of Pulmonary Vascular Disease -- Artificial Intelligence Based Evaluation of the Aorta -- Artificial Intelligence and Radiomics Based Evaluation of Carotid Artery Disease -- PART V: Artificial Intelligence: General Considerations -- Artificial Intelligence in Medicine: Laws, Regulations and Privacy -- Health Economics, Economic Evaluation and Artificial Intelligence Technology -- Commercialization & Intellectual Property of Artificial Intelligence Applications in Cardiovascular Imaging -- Ethical Considerations of Artificial Intelligence Applications in Healthcare -- How to Write and Review an Artificial Intelligence Paper -- Cybersecurity in the Era of Artificial Intelligence -- How Artificial Intelligence Will Reshape Healthcare and Medical Imaging: A Global Perspective. |
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| | This book provides an overview of current and potential applications of artificial intelligence (AI) for cardiothoracic imaging. Most AI systems used in medical imaging are data-driven and based on supervised machine learning. Clinicians and AI specialists can contribute to the development of an AI system in different ways, focusing on their respective strengths. Unfortunately, communication between these two sides is far from fluent and, from time to time, they speak completely different languages. Mutual understanding and collaboration are imperative because the medical system is based on physicians’ ability to take well-informed decisions and convey their reasoning to colleagues and patients. This book offers unique insights and informative chapters on the use of AI for cardiothoracic imaging from both the technical and clinical perspective. It is also a single comprehensive source that provides a complete overview of the entire process of the development and use of AI in clinical practice for cardiothoracic imaging. The book contains chapters focused on cardiac and thoracic applications as well more general topics on the potentials and pitfalls of AI in medical imaging. Separate chapters will discuss the valorization, regulations surrounding AI, cost-effectiveness, and future perspective for different countries and continents. This book is an ideal guide for clinicians (radiologists, cardiologists etc.) interested in working with AI, whether in a research setting developing new AI applications or in a clinical setting using AI algorithms in clinical practice. The book also provides clinical insights and overviews for AI specialists who want to develop clinically relevant AI applications. |
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| DOI: | doi:10.1007/978-3-030-92087-6 |
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| URL: | Resolving-System: https://doi.org/10.1007/978-3-030-92087-6 |
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| | DOI: https://doi.org/10.1007/978-3-030-92087-6 |
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| Schlagwörter: | (s)Künstliche Intelligenz / (s)Kardiovaskuläres System / (s)Bildanalyse / (s)Diagnostik |
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| | (s)Künstliche Intelligenz / (s)Radiologie |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Bibliogr. Hinweis: | Erscheint auch als : Druck-Ausgabe |
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| | Erscheint auch als : Druck-Ausgabe |
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| | Erscheint auch als : Druck-Ausgabe |
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| | Erscheint auch als : Druckausgabe: Artificial intelligence in cardiothoracic imaging. - Cham : Humana Press, 2022. - XXIV, 595 Seiten |
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| K10plus-PPN: | 1800272790 |
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| Lokale URL UB: |  Zum Volltext |
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| | Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg |
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| |  Bestellen/Vormerken für Benutzer des Klinikums Mannheim
Eigene Kennung erforderlich |
| Bibliothek/Idn: | UW / m412258616X |
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| Lokale URL Inst.: | Zum Volltext |
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Artificial Intelligence in Cardiothoracic Imaging / De Cecco, Carlo N. [HerausgeberIn]; 2022. (Online-Ressource)
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