Over the last decade, some of the greatest achievements in the field of neuroimaging have been related to remarkable advances in magnetic resonance techniques, including diffusion, perfusion, magnetic resonance spectroscopy, and functional MRI. Such techniques have provided valuable insights into tissue microstructure, microvasculature, metabolism and brain connectivity. Previously available mostly in research environments, these techniques are now becoming part of everyday clinical practice in a plethora of clinical MR systems. Nevertheless, despite growing interest and wider acceptance, there remains a lack of a comprehensive body of knowledge on the subject, exploring the intrinsic complexity and physical difficulty of the techniques. This book focuses on the basic principles and theories of diffusion, perfusion, magnetic resonance spectroscopy, and functional MRI. It also explores their clinical applications and places emphasis on the associated artifacts and pitfalls with a comprehensive and didactic approach. This book aims to bridge the gap between research applications and clinical practice. It will serve as an educational manual for neuroimaging researchers and radiologists, neurologists, neurosurgeons, and physicists with an interest in advanced MR techniques. It will also be a useful reference text for experienced clinical scientists who wish to optimize their multi-parametric imaging approach.

This book is an ideal introduction to the specialty of post mortem computed tomography (PMCT). It will serve as a comprehensive yet accessible guide to the understanding and interpretation of whole-body studies for both hospital and community settings. Both normal post mortem appearances and findings associated with a wide range of diagnoses encountered in real cases from the coronial service are presented with the aid of numerous images. The coverage encompasses not only findings in all anatomic regions but also the imaging appearances in cases following targeted coronary angiography, attempted cardiopulmonary resuscitation and various special circumstances such as suicide. The inclusion of many practical tips and possible pitfalls will support the radiologist to become more confident when reporting PMCT, while for the more experienced practitioner the wealth of examples will serve as a useful resource. In addition to radiologists, the book will be of value for pathologists at all levels of experience and anyone needing to understand the role and limitations of PMCT.

This book focuses on congenital heart disease (CHD) and emerging imaging technologies. It covers all clinically relevant aspects of the fascinating new cardiac imaging technologies, including a comprehensive explanation of their basic principles, practical aspects of novel clinical applications, and detailed descriptions of specific uses in the broad spectrum of clinically important adult CHD. Innovations and emerging technologies for diagnosis and therapeutics, evaluation and treatment are continually evolving, and due to these advances in non-invasive diagnosis, there has been a significant improvement in the survival rates for CHD patient. Novel approaches to trans-catheter interventions and advances in echocardiography, MRI and CT imaging are being developed and incorporated into routine clinical practice, while emerging three-dimensional printing technologies are fundamentally affecting patient care, research, trainee education, and interactions between multidisciplinary teams, patients, and caregivers. In addition, translational technologies on the horizon promise to take this nascent field even further. Exploring the applicability of these emerging technologies in improving our understanding of complex congenital cardiac defect anatomy and physiology will provide new treatment options for this unique population. Written by experts in the field who are also involved in patient care, this book discusses the practical application of innovations in advanced multimodality imaging in the daily clinical routine and offers tips and tricks for beginners.

Stay on top of recent, significant changes in the areas of nuclear medicine and molecular imaging with this updated and expanded volume in the popular Case Review Series. Nuclear Medicine and Molecular Imaging, 3rd Edition offers highly illustrated, case-based preparation for board review to help residents and recertifying radiologists succeed on exams and provide state-of-the-art patient care. Presents 150 case studies organized by level of difficulty, with all new multiple-choice questions, answers, and rationales that mimic the format of certification exams. Provides more cases on positron emission tomography (PET), including all the latest applications of PET/CT hybrid imaging. Covers new tracers such as Ga68 DOTA, F-18 amyloid, and F-18 prostate cancer imaging agents as well as new indications for Tc99m sestamibi. Reflects recent changes in nuclear medicine including information on patient selection, how therapy affects patients, and if there is evidence of recurring disease. Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.

A unique resource, this book is designed to determine not only your level of expertise and applicability of knowledge but also serve as an up-to-date clinical resource in the practice of cardiac sonography. This powerful, long-needed resource presents the essentials of clinical echocardiography in a precise Q&A format fashioned after Clinical Echocardiography Review A Self-Assessment Tool edited by Allan L. Klein and Craig R. Asher. Whether you are just beginning your training, are already preparing for your examination, or simply want to review and increase your knowledge depth, this easy-to-use resource will help you develop the knowledge and skills you need for success. Flexible: A wide range of multiple-choice questions identified as beginner, intermediate, or advanced make it easy for you to select the level of material you want to review. Quick-review format: Concise chapters by experts in the field follow an easy-to-follow, Q&A style to ensure content mastery. Concise Answer Outlines: Each question is supported by a detailed answer outline to enhance understanding and skill development. Visual: More than 400 online echo clip videos bring concepts and techniques to life and help you to internalize key essential elements of disease recognition. Clinically Oriented: More than 1,270 self-assessment questions (many with case-based images and easily accessible video files) place you in clinical scenarios. Practical: An extensive online question bank gives you unlimited opportunities for self-assessment and review. Enrich Your eBook Reading Experience Read directly on your preferred device(s), such as computer, tablet, or smartphone Easily convert to audiobook, powering your content with natural language text-to-speech

This book constitutes the Second International Challenge on Kidney and Kidney Tumor Segmentation, KiTS 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021. The challenge took place virtually on September 27, 2021, due to the COVID-19 pandemic. The 21 contributions presented were carefully reviewed and selected from 29 submissions. This challenge aims to develop the best system for automatic semantic segmentation of renal tumors and surrounding anatomy.

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.

This book covers relevant concepts in nuclear cardiology, combining imaging techniques and clinical data to do so. Today, nuclear cardiology is a worldwide discipline connected to the broader field of cardiovascular imaging. The combination of clinical aspects (symptoms, medications, previous cardiac procedures), ancillary exams and nuclear images is key to decision-making in clinical practice. Thus, a book on this topic is essential to provide better outcomes for cardiology patients. The chapters cover a comprehensive range of topics in current cardiology practice, such as ambulatory patients, patients in emergency settings, patients after complex cardiac procedures, and patients during and after the use of cancer therapies that are potentially toxic for the heart (cardio-oncology). As such, multiple clinical scenarios are also presented: patients with suspected coronary disease, patients with heart failure of unknown origin, patients with acute chest pain in the emergency department, patients with suspected pulmonary embolism, patients with complications of the left ventricular assist device, etc. Furthermore, the book describes nuclear cardiology procedures and techniques, discusses the main clinical indications and scenarios for each procedure, presents new technological advances in the field (machine learning and artificial intelligence tools), and mentions the coronavirus disease 2019 (COVID-19) pandemic. Given its scope, the book offers a valuable guide and videos for various medical professionals, especially cardiologists and nuclear physicians.

This book constitutes the Second Automatization of Cranial Implant Design in Cranioplasty Challenge, AutoImplant 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September, 2021. The challenge took place virtually due to the COVID-19 pandemic. The 7 papers are presented together with one invited paper, one qualitative evaluation criteria from neurosurgeons and a dataset descriptor. This challenge aims to provide more affordable, faster, and more patient-friendly solutions to the design and manufacturing of medical implants, including cranial implants, which is needed in order to repair a defective skull from a brain tumor surgery or trauma. The presented solutions can serve as a good benchmark for future publications regarding 3D volumetric shape learning and cranial implant design.

This book constitutes the refereed joint proceedings of the 11th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in October 2021. The workshop was held virtually due to the COVID-19 pandemic.The 10 full papers presented at ML-CDS 2021 were carefully reviewed and selected from numerous submissions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning.

Imaging for nurses is a practical guide for nurses in imaging departments and for all clinical nurse specialists caring for patients undergoing imaging procedures and investigations e.g. in the areas of cardiology, vascular interventions, accident and emergency, urology, neurology, and gastro-intestinal medicine
Imaging for nurses addresses all aspects of nursing care including patient preparation, imaging procedures, and post-procedure care. It provides a clear introduction to essential imaging theory and the role and responsibilities of the nurse in imaging procedures. Separate chapters cover fluoroscopy, ultrasound, computerised tomography, magnetic resonance imaging and use of radioisotopes for ease of reference.

This book constitutes the refereed proceedings of the Third International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2021, and the 6th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2021, held in conjunction with MICCAI 2021. The conference was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic.For UNSURE 2021, 13 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. PIPPI 2021 accepted 14 papers from the 18 submissions received. The workshop aims to bring together methods and experience from researchers and authors working on these younger cohorts and provides a forum for the open discussion of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period.

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging - others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2021, held on September 27, 2021, in conjunction with MICCAI 2021. The workshop was held virtually due to the COVID-19 pandemic. The 17 papers presented in this book were carefully reviewed and selected from 27 submissions. They were organized in topical sections named: computational anatomy and brain networks and time series.

Over the past few decades there have been major advances in computed tomography (CT) to improve the performance of cardiac imaging. Thanks to the improved scanning speed, power boost tubes, and increased-width detectors, the latest CT technology delivers greater coverage, better spatial and temporal resolution, and functional information on cardiac diseases. Focusing on cardiac CT imaging, this book offers case-based information on cardiac diseases, presents the current technical status, and highlights applications, helping readers systematically understand how cardiac CTs are performed and interpreted in clinical practice. Divided into six chapters, it broadly discusses the characteristics of CT imaging and its applications to coronary artery disease (CAD); non-atherosclerotic coronary artery disease; congenital heart disease; cardiac neoplasms; cardiomyopathy and aortic diseases.

This book constitutes the proceedings of the 27th International Conference on Information Processing in Medical Imaging, IPMI 2021, which was held online during June 28-30, 2021. The conference was originally planned to take place in Bornholm, Denmark, but changed to a virtual format due to the COVID-19 pandemic. The 59 full papers presented in this volume were carefully reviewed and selected from 200 submissions. They were organized in topical sections as follows: registration; causal models and interpretability; generative modelling; shape; brain connectivity; representation learning; segmentation; sequential modelling; learning with few or low quality labels; uncertainty quantification and generative modelling; and deep learning.

This textbook, intended for advanced undergraduate and graduate students, is an introduction to the physical and mathematical principles used in clinical medical imaging. The first two chapters introduce basic concepts and useful terms used in medical imaging and the tools implemented in image reconstruction, while the following chapters cover an array of topics such as physics of x-rays and their implementation in planar and computed tomography (CT) imaging; nuclear medicine imaging and the methods of forming functional planar and single photon emission computed tomography (SPECT) images and Clinical imaging using positron emitters as radiotracers. The book also discusses the principles of MRI pulse sequencing and signal generation, gradient fields, and the methodologies implemented for image formation, form flow imaging and magnetic resonance angiography and the basic physics of acoustic waves, the different acquisition modes used in medical ultrasound, and the methodologies implemented for image formation and flow imaging using the Doppler Effect. By the end of the book, readers will know what is expected from a medical image, will comprehend the issues involved in producing and assessing the quality of a medical image, will be able to conceptually implement this knowledge in the development of a new imaging modality, and will be able to write basic algorithms for image reconstruction. Knowledge of calculus, linear algebra, regular and partial differential equations, and a familiarity with the Fourier transform and it applications is expected, along with fluency with computer programming. The book contains exercises, homework problems, and sample exam questions that are exemplary of the main concepts and formulae students would encounter in a clinical setting.

Cardiac implantable device (CIED) infections are a key issue since they have serious consequences in terms of morbidity, mortality and associated costs for healthcare systems. Such infections are highly complex, which has implications for prevention (several factors underlie its development), diagnosis (requiring patient specific integration of several elements), acute treatment (choice of the antibiotic, lead extraction procedure), as well as long-term management (CIED re-implantation strategy and follow-up). Dealing with CIED infections requires appropriate organization of healthcare provision, with the creation of integrated hub-spoke referrals, and it has prompted many of the recent developments in CIED technologies: leadless pacemakers, subcutaneous defibrillators, antibacterial envelops and lead extraction devices. This book systematically examines all aspects of this multifaceted condition, discussing each clinical and organizational issue in a separate self-contained chapter. It starts by reviewing the epidemiology/pathophysiology of CIED infections, and then addresses acute and long-term management. Offering a comprehensive overview of the prevention of infections, considering both current and future perspectives, the book also provides practical suggestions along with recommendations from the literature in the field. This is the first book entirely focused on CIED infections. Written by an international team of leading experts it will appeal to broad audience, including cardiologists, electrophysiologists, infectious disease specialists, internists, healthcare professionals, health service managers and providers, researchers and those working in industries involved in the field.

This book constitutes the refereed proceedings of the 5th International Workshop and Challenge on Computational Methods and Clinical Applications for Musculoskeletal Imaging, MSKI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 13 workshop papers were carefully reviewed and selected for inclusion in this volume. Topics of interest include all major aspects of musculoskeletal imaging, for example: clinical applications of musculoskeletal computational imaging; computer-aided detection and diagnosis of conditions of the bones, muscles and joints; image-guided musculoskeletal surgery and interventions; image-based assessment and monitoring of surgical and pharmacological treatment; segmentation, registration, detection, localization and visualization of the musculoskeletal anatomy; statistical and geometrical modeling of the musculoskeletal shape and appearance; image-based microstructural characterization of musculoskeletal tissue; novel techniques for musculoskeletal imaging.