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020 _a9783030920876
024 7 _a10.1007/978-3-030-92087-6
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aRC941
_b2022 EB
245 0 0 _aArtificial Intelligence in Cardiothoracic Imaging
_cedited by Carlo N. De Cecco, Marly van Assen, Tim Leiner
250 _aFirst edition 2022
264 1 _aCham
_bSpringer International Publishing
_c2022
300 _a1 recurso en línea (XXIV, 595 páginas)
_b233 ilustraciones, 200 ilustraciones a color
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aContemporary Medical Imaging
_x2626-6423
505 0 _aPART 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.
520 _aThis 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.
988 _aSpringer_Medicine_2022
650 7 _2embne
_9202747
_aTórax
_xDiagnóstico por imagen
700 1 _aDe Cecco, Carlo N
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _avan Assen, Marly
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLeiner, Tim
_eeditor literario
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030920869
776 0 8 _iPrinted edition:
_z9783030920883
776 0 8 _iPrinted edition:
_z9783030920890
830 0 _aContemporary Medical Imaging,
_x2626-6423
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-92087-6
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b09/2022
_dz
_eIG
_zSI