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Artificial intelligence in cardiothoracic imaging / / edited by Carlo N. De Cecco, Marly van Assen, and Tim Leiner
| Artificial intelligence in cardiothoracic imaging / / edited by Carlo N. De Cecco, Marly van Assen, and Tim Leiner |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (582 pages) |
| Disciplina | 617.540754028563 |
| Collana | Contemporary medical imaging series |
| Soggetto topico |
Chest - Imaging
Artificial intelligence - Medical applications Heart Diseases - diagnostic imaging Artificial Intelligence Image Interpretation, Computer-Assisted - methods Thoracic Diseases - diagnostic imaging Tòrax Malalties del tòrax Malalties del cor Diagnòstic per la imatge Intel·ligència artificial |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-92087-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910564686703321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Atlas of chest imaging in COVID-19 patients / / Jinxin Liu, Xiaoping Tang, Chunliang Lei, editors
| Atlas of chest imaging in COVID-19 patients / / Jinxin Liu, Xiaoping Tang, Chunliang Lei, editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XII, 192 p. 165 illus., 6 illus. in color.) |
| Disciplina | 617.540754 |
| Soggetto topico |
Chest - Imaging
COVID-19 Imatges mèdiques |
| Soggetto genere / forma |
Atles (Científic)
Llibres electrònics |
| ISBN | 981-16-1082-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Overview of COVID-19 Pneumonia -- Common CT Features of COVID-19 Pneumonia -- CT Features of Early COVID-19 Pneumonia (PCR-positive) -- CT features of intermediate stage of COVID-19 Pneumonia -- CT Features of late stage of COVID-19 Pneumonia -- Chest Features of Severe and Critical Patients with COVID-19 Pneumonia -- Role of CT and CT features of Suspected COVID-19 Patients (PCR negative) -- Follow-up CT of Patients with First Negative CT but Positive PCR for COVID-19 -- Imaging Analysis of Family Clustering -- Residual CT Features in Recovery stage of COVID-19 Pneumonia. |
| Record Nr. | UNINA-9910483011603321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Diagnostic Imaging of the Chest / / by: Wormanns, Dag
| Diagnostic Imaging of the Chest / / by: Wormanns, Dag |
| Autore | Biederer Jürgen |
| Pubbl/distr/stampa | Stuttgart : , : Thieme, , 2020 |
| Descrizione fisica | 1 online resource (364 pages) |
| Disciplina | 616.2004754 |
| Soggetto topico |
Respiratory organs - Imaging
Chest - Imaging Diagnostic imaging |
| ISBN |
3-13-258243-3
3-13-241566-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Examination Technique -- Basic Anatomy -- General Symptomatology -- Indications -- Pneumonia -- Diffuse Parenchymal Lung Diseases -- Immunologic Diseases of the Lung -- Chronic Obstructive Pulmonary Disease -- Tumors of the Lung -- Airway Diseases -- Pleural Diseases -- Mediastinal Diseases -- Diseases of the Chest Wall and Diaphragm -- Vascular Diseases -- Chest Trauma -- Diagnostic Imaging of the Chest in Intensive Care Medicine -- Treatment-Related Changes -- Occupational Lung Diseases -- Congenital Thoracic Diseases and Malformations -- Nonvascular Interventions -- Pulmonary Nodules -- Cavities -- Persistent or Migratory Pulmonary Infiltrates -- Diagnostic Schema for Typical Computed Tomography Findings of Diffuse Pulmonary Diseases -- Fleischner Society Glossary of Terms for Thoracic Imaging. |
| Record Nr. | UNINA-9910795374803321 |
Biederer Jürgen
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| Stuttgart : , : Thieme, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Diagnostic Imaging of the Chest / / by: Wormanns, Dag
| Diagnostic Imaging of the Chest / / by: Wormanns, Dag |
| Autore | Biederer Jürgen |
| Pubbl/distr/stampa | Stuttgart : , : Thieme, , 2020 |
| Descrizione fisica | 1 online resource (364 pages) |
| Disciplina | 616.2004754 |
| Soggetto topico |
Respiratory organs - Imaging
Chest - Imaging Diagnostic imaging |
| ISBN |
3-13-258243-3
3-13-241566-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Examination Technique -- Basic Anatomy -- General Symptomatology -- Indications -- Pneumonia -- Diffuse Parenchymal Lung Diseases -- Immunologic Diseases of the Lung -- Chronic Obstructive Pulmonary Disease -- Tumors of the Lung -- Airway Diseases -- Pleural Diseases -- Mediastinal Diseases -- Diseases of the Chest Wall and Diaphragm -- Vascular Diseases -- Chest Trauma -- Diagnostic Imaging of the Chest in Intensive Care Medicine -- Treatment-Related Changes -- Occupational Lung Diseases -- Congenital Thoracic Diseases and Malformations -- Nonvascular Interventions -- Pulmonary Nodules -- Cavities -- Persistent or Migratory Pulmonary Infiltrates -- Diagnostic Schema for Typical Computed Tomography Findings of Diffuse Pulmonary Diseases -- Fleischner Society Glossary of Terms for Thoracic Imaging. |
| Record Nr. | UNINA-9910813088103321 |
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Biederer Jürgen
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| Stuttgart : , : Thieme, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning chest imaging / / John C. Pedrozo Pupo (editor)
| Learning chest imaging / / John C. Pedrozo Pupo (editor) |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2013 |
| Descrizione fisica | 1 online resource (253 p.) |
| Disciplina | 617.5/40757 |
| Altri autori (Persone) | Pedrozo PupoJohn C |
| Collana | Learning imaging |
| Soggetto topico |
Chest - Imaging
Diagnostic imaging |
| ISBN | 3-642-34147-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Pleural and Pleural Space -- Diaphragm -- Mediastinum and Pulmonary Circulation -- Air Space, and Bronchi I -- Air Space, and Bronchi II -- Trachea and Airway -- Heart and Great Vessels -- Chest Wall and Soft Tissues -- Pulmonary Interstitium -- Medical Device, and Monitoring of the Chest. |
| Record Nr. | UNINA-9910437984803321 |
| Berlin ; ; New York, : Springer, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Multi-modality cardiac imaging : processing and analysis / / edited by Patrick Clarysse, Denis Friboulet
| Multi-modality cardiac imaging : processing and analysis / / edited by Patrick Clarysse, Denis Friboulet |
| Pubbl/distr/stampa | London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 616.120757 |
| Collana | Digital Signal and Image Processing Series |
| Soggetto topico |
Heart - Imaging
Cardiovascular system - Imaging Chest - Imaging |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-118-57446-X
1-118-57442-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Table of Contents; Title; Copyright; Preface; Acknowledgements; Introduction; PART 1: Methodological Bases; 1 Extraction and Segmentation of Structures in Image Sequences; 1.1 Problematics; 1.2 Overview of segmentation methods; 1.3. Summary of the different classes of deformable models; 1.4. Deformable templates; 1.5. Variational active contours; 1.6. Integration of a priori constraints in the formalism of variational contours; 1.7. Implementation examples in cardiac imaging; 1.8. Conclusion; 1.9. Bibliography; 2 Motion Estimation and Analysis; 2.1. Problematics; 2.2. Problem formulation
2.3. Transport methods2.4. Probabilistic approaches; 2.5. Image registration; 2.6. Local methods; 2.7. Hybrid methods; 2.8. Phase-based methods; 2.9. Registration and motion estimation in a sequence of images; 2.10. Evaluation of motion estimation methods; 2.11. Conclusion; 2.12. Bibliography; 3 Post-processing and Analysis of Dynamic Magnetic Resonance Images for Myocardial Perfusion Quantification; 3.1. Introduction; 3.2. Dynamic measurement of perfusion with contrast agents: reminder about the MRI sequences and the different contrast agents used 3.3. Motion correction and contour segmentation of the myocardium: important preprocessing prior to quantitative analysis3.4. Semi-quantitative perfusion analysis: calculation of relative parameters depending on the injection of the contrast medium; 3.5. Absolute parameters independent of the contrast agent injection (taking account of the arterial input): pharmacokinetic modeling; 3.6. Conclusion; 3.7. Bibliography; 4 Tensor Decomposition of a Dynamic Sequence of Images into Simple Elements; 4.1. Problematics; 4.2. Panorama of methods for the quantitative analysis of dynamic image sequences 4.3. Tensor decomposition methods of an image sequence into simple elements4.4. Specifications for radiotracer or contrast medium monitoring; 4.5. Specifications for the study of cardiac motion; 4.6. Conclusion; 4.7. Bibliography; PART 2: Application Examples; 5 Evaluation of Cardiac Structure Segmentation in Cine Magnetic Resonance Imaging; 5.1. Context: significance of the automatic segmentation of the cardiac structures; 5.2. Evaluation necessity; 5.3. Empirical evaluation methods; 5.4. Visual evaluation methods; 5.5. Supervised methods; 5.6. Non-supervised evaluation methods 5.7. Conclusion5.8. IMPEIC and MEDIEVAL working groups; 5.9. Bibliography; 6 Phase-based Heart Motion Estimation in Multimodality Cardiac Imaging; 6.1. Phase images; 6.2. Optical flow motion estimation on the phase of the two single-orthant analytic signals and using a deformable mesh: application to cardiac MRI sequences; 6.3. Motion estimation by optical flow from the monogenic phase using a local affine model and multiscale analysis - application to ultrasonic cardiac sequences; 6.4. Bibliography; 7 Cardiac Motion Analysis in Tagged MRI; 7.1. Motion quantification by the SinMod method 7.2. Processing pipeline and features of the software inTag |
| Record Nr. | UNINA-9910131450203321 |
| London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Multi-modality cardiac imaging : processing and analysis / / edited by Patrick Clarysse, Denis Friboulet
| Multi-modality cardiac imaging : processing and analysis / / edited by Patrick Clarysse, Denis Friboulet |
| Pubbl/distr/stampa | London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 |
| Descrizione fisica | 1 online resource (313 p.) |
| Disciplina | 616.120757 |
| Collana | Digital Signal and Image Processing Series |
| Soggetto topico |
Heart - Imaging
Cardiovascular system - Imaging Chest - Imaging |
| ISBN |
1-118-57446-X
1-118-57442-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Table of Contents; Title; Copyright; Preface; Acknowledgements; Introduction; PART 1: Methodological Bases; 1 Extraction and Segmentation of Structures in Image Sequences; 1.1 Problematics; 1.2 Overview of segmentation methods; 1.3. Summary of the different classes of deformable models; 1.4. Deformable templates; 1.5. Variational active contours; 1.6. Integration of a priori constraints in the formalism of variational contours; 1.7. Implementation examples in cardiac imaging; 1.8. Conclusion; 1.9. Bibliography; 2 Motion Estimation and Analysis; 2.1. Problematics; 2.2. Problem formulation
2.3. Transport methods2.4. Probabilistic approaches; 2.5. Image registration; 2.6. Local methods; 2.7. Hybrid methods; 2.8. Phase-based methods; 2.9. Registration and motion estimation in a sequence of images; 2.10. Evaluation of motion estimation methods; 2.11. Conclusion; 2.12. Bibliography; 3 Post-processing and Analysis of Dynamic Magnetic Resonance Images for Myocardial Perfusion Quantification; 3.1. Introduction; 3.2. Dynamic measurement of perfusion with contrast agents: reminder about the MRI sequences and the different contrast agents used 3.3. Motion correction and contour segmentation of the myocardium: important preprocessing prior to quantitative analysis3.4. Semi-quantitative perfusion analysis: calculation of relative parameters depending on the injection of the contrast medium; 3.5. Absolute parameters independent of the contrast agent injection (taking account of the arterial input): pharmacokinetic modeling; 3.6. Conclusion; 3.7. Bibliography; 4 Tensor Decomposition of a Dynamic Sequence of Images into Simple Elements; 4.1. Problematics; 4.2. Panorama of methods for the quantitative analysis of dynamic image sequences 4.3. Tensor decomposition methods of an image sequence into simple elements4.4. Specifications for radiotracer or contrast medium monitoring; 4.5. Specifications for the study of cardiac motion; 4.6. Conclusion; 4.7. Bibliography; PART 2: Application Examples; 5 Evaluation of Cardiac Structure Segmentation in Cine Magnetic Resonance Imaging; 5.1. Context: significance of the automatic segmentation of the cardiac structures; 5.2. Evaluation necessity; 5.3. Empirical evaluation methods; 5.4. Visual evaluation methods; 5.5. Supervised methods; 5.6. Non-supervised evaluation methods 5.7. Conclusion5.8. IMPEIC and MEDIEVAL working groups; 5.9. Bibliography; 6 Phase-based Heart Motion Estimation in Multimodality Cardiac Imaging; 6.1. Phase images; 6.2. Optical flow motion estimation on the phase of the two single-orthant analytic signals and using a deformable mesh: application to cardiac MRI sequences; 6.3. Motion estimation by optical flow from the monogenic phase using a local affine model and multiscale analysis - application to ultrasonic cardiac sequences; 6.4. Bibliography; 7 Cardiac Motion Analysis in Tagged MRI; 7.1. Motion quantification by the SinMod method 7.2. Processing pipeline and features of the software inTag |
| Record Nr. | UNINA-9910830396303321 |
| London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Thoracic image analysis : second international workshop,TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Jens Petersen [and seven others] (editors)
| Thoracic image analysis : second international workshop,TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Jens Petersen [and seven others] (editors) |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (X, 166 p. 63 illus., 49 illus. in color.) |
| Disciplina | 617.540757 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Chest - Imaging |
| ISBN | 3-030-62469-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Multi-cavity Heart Segmentation in Non-contrast Non-ECG Gated CT Scans with F-CNN -- 3D Deep Convolutional Neural Network-based Ventilated Lung Segmentation using Multi-nuclear Hyperpolarized Gas MRI -- Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet -- 3D Probabilistic Segmentation and Volumetry from 2D Projection Images -- CovidDiagnosis: Deep Diagnosis of Covid-19 Patients using Chest X-rays -- Can We Trust Deep Learning Based Diagnosis? The Impact of Domain Shift in Chest Radiograph Classification -- A Weakly Supervised Deep Learning Framework for COVID-19 CT Detection and Analysis -- Deep Reinforcement Learning for Localization of the Aortic Annulus in Patients with Aortic Dissection -- Functional-Consistent CycleGAN for CT to Iodine Perfusion Map Translation -- MRI to CTA Translation for Pulmonary Artery Evaluation using CycleGANs Trained with Unpaired Data -- Semi-supervised Virtual Regression of Aortic Dissections Using 3D Generative Inpainting -- Registration-Invariant Biomechanical Features for Disease Staging of COPD in SPIROMICS -- Deep Group-wise Variational Diffeomorphic Image Registration. |
| Record Nr. | UNISA-996418217403316 |
| Cham, Switzerland : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Thoracic image analysis : second international workshop,TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Jens Petersen [and seven others] (editors)
| Thoracic image analysis : second international workshop,TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, proceedings / / Jens Petersen [and seven others] (editors) |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (X, 166 p. 63 illus., 49 illus. in color.) |
| Disciplina | 617.540757 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Chest - Imaging |
| ISBN | 3-030-62469-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Multi-cavity Heart Segmentation in Non-contrast Non-ECG Gated CT Scans with F-CNN -- 3D Deep Convolutional Neural Network-based Ventilated Lung Segmentation using Multi-nuclear Hyperpolarized Gas MRI -- Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet -- 3D Probabilistic Segmentation and Volumetry from 2D Projection Images -- CovidDiagnosis: Deep Diagnosis of Covid-19 Patients using Chest X-rays -- Can We Trust Deep Learning Based Diagnosis? The Impact of Domain Shift in Chest Radiograph Classification -- A Weakly Supervised Deep Learning Framework for COVID-19 CT Detection and Analysis -- Deep Reinforcement Learning for Localization of the Aortic Annulus in Patients with Aortic Dissection -- Functional-Consistent CycleGAN for CT to Iodine Perfusion Map Translation -- MRI to CTA Translation for Pulmonary Artery Evaluation using CycleGANs Trained with Unpaired Data -- Semi-supervised Virtual Regression of Aortic Dissections Using 3D Generative Inpainting -- Registration-Invariant Biomechanical Features for Disease Staging of COPD in SPIROMICS -- Deep Group-wise Variational Diffeomorphic Image Registration. |
| Record Nr. | UNINA-9910427674303321 |
| Cham, Switzerland : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Thoracic imaging : a core review / / editors, Stephen B. Hobbs, Christian W. Cox
| Thoracic imaging : a core review / / editors, Stephen B. Hobbs, Christian W. Cox |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Philadelphia, Pennsylvania : , : Wolters Kluwer, , 2021 |
| Descrizione fisica | 1 online resource (935 pages) |
| Disciplina | 617.540754 |
| Soggetto topico | Chest - Imaging |
| ISBN |
1-9751-2625-4
1-9751-2624-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intro -- Half Title -- Title -- Copyright -- Dedication -- Contributors -- Series Foreword -- Preface -- Contents -- Acknowledgments -- 1: Basics of Imaging -- 2: Normal Anatomy -- 3: Terms and Signs -- 4: Intensive Care Unit Radiographs -- 5: Infectious Pneumonia -- 6: Diffuse Lung Disease -- 7: Diffuse Alveolar Disease and Inflammatory Conditions -- 8: Airway Disease -- 9: Thoracic Manifestations of Systemic Disease -- 10: Atelectasis and Collapse -- 11: Pulmonary Physiology -- 12: Diseases of the Pleura, Chest Wall, and Diaphragm -- 13: Mediastinal Disease -- 14: Vascular Disease -- 15: Lung Cancer -- 16: Trauma -- 17: Congenital Disease -- 18: Postoperative Thorax -- Index. |
| Record Nr. | UNINA-9910794475803321 |
| Philadelphia, Pennsylvania : , : Wolters Kluwer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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