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.

This is an introduction to recent developments in the application of wave-splitting methods to direct and inverse scattering of wave fields. Here wave-splitting refers to the decomposition of the total field into two components which propagate in opposite directions. Although the text emphasizes time domain methods, it includes some applications to frequency domain problems.

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.

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.

Single Molecule Science (SMS) has emerged from developing, using and combining technologies such as super-resolution microscopy, atomic force microscopy, and optical and magnetic tweezers, alongside sophisticated computational and modelling techniques. This comprehensive, edited volume brings together authoritative overviews of these methods from a biological perspective, and highlights how they can be used to observe and track individual molecules and monitor molecular interactions in living cells. Pioneers in this fast-moving field cover topics such as single molecule optical maps, nanomachines, and protein folding and dynamics. A particular emphasis is also given to mapping DNA molecules for diagnostic purposes, and the study of gene expression. With numerous illustrations, this book reveals how SMS has presented us with a new way of understanding life processes. A must-have for researchers and graduate students, as well as those working in industry, primarily in the areas of biophysics, biological imaging, genomics and structural biology.

The constant advances in diagnostic imaging have had an impact on the practice, attitudes, and moral values of all who participate in health care. Now in its fourth edition, the original Medicolegal Issues for Radiographers has been updated and retitled, broadening the scope of content to include issues essential to all diagnostic imaging professionals. Medicolegal Issues for Diagnostic Imaging Professionals, Fourth Edition provides readers with a basic understanding of the important legal definitions, legal doctrines, malpractice and risk management information, ethics and patient rights relevant to the field of diagnostic imaging and the role of the imaging professional. It includes case histories in the form of vignettes that assist readers in applying the principles of law to real work situations. The vignettes can stimulate discussion, raise other related issues, and supply a broadened perspective on the various facets of the questions presented. New in this Edition: Expanded discussion on evidence More detail on the ramifications of the Civil Rights Act of 1991 Updated information on licensure, certification, and credentialing Entirely new discussions on: Morality, ethics, and the law Deontology Beneficence and nonmaleficence Right of autonomy Confidentiality Liability for disclosure of confidential information HIPPA ARRT Euthanasia Humanistic Health Care Teleradiology Twelve years since its initial publication, this medical legal text remains a bestseller. By reviewing the materials in this seminal volume, imaging professionals, radiologists, and radiologic technologists stay abreast of important legal issues and are better able to avoid the scourge of a malpractice suit.

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 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.

Selected as a Doody's Core Title for 2022! Packing essential abdominal imaging protocols in a compact format, this handy reference makes it easy to access the most up-to-date protocols, organ-specific measurements, and echogenicities for abdominal sonography. Organized logically by the organs of the abdomen, this succinct, image-based quick-reference presents imaging and line drawings side-by-side to help you make confident, accurate observations. Up-to-date protocol guidelines reflect the most current clinical approaches and relevant research. Organ-based organization provides fast access to patient preparation and suggested transducer, scanning tips, laboratory values tables, sonography anatomy, common pathology and references in each section. Concise, pocket-sized presentation puts essential information at your fingertips from the sonography lab to the point of imaging. Side-by-side imaging and line drawings reinforce your understanding and ensure the most accurate imaging observations. "Cine" loop short video clips clarify normal anatomy in vibrant detail. eBook available for purchase. Fast, smart, and convenient, today's eBooks can transform learning. These interactive, fully searchable tools offer 24/7 access on multiple devices, the ability to highlight and share notes, and more

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.

Mit neu entwickelten diagnostischen Moeglichkeiten und verbesserten Therapieverfahren ist eine zunehmend differenzierte Behandlung von Lungenmetastasen boesartiger Tumoren moeglich geworden. Je nach Ursprungstumor und klinischer Situation wird ein unterschiedliches Vorgehen empfohlen. Neben onkologischen Gesichtspunkten ruckt auch die verbleibende Lungenfunktion in den Mittelpunkt des Interesses. Die moderne Bildgebung, offene und minimal invasive Operationsverfahren und interdisziplinare Therapiekonzepte zu den einzelnen Tumorentitaten sind detailliert und praxisorientiert beschrieben.

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 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 two-volume set LNCS 12658 and 12659 constitutes the thoroughly refereed proceedings of the 6th International MICCAI Brainlesion Workshop, BrainLes 2020, the International Multimodal Brain Tumor Segmentation (BraTS) challenge, and the Computational Precision Medicine: Radiology-Pathology Challenge on Brain Tumor Classification (CPM-RadPath) challenge. These were held jointly at the 23rd Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2020, in Lima, Peru, in October 2020.* The revised selected papers presented in these volumes were organized in the following topical sections: brain lesion image analysis (16 selected papers from 21 submissions); brain tumor image segmentation (69 selected papers from 75 submissions); and computational precision medicine: radiology-pathology challenge on brain tumor classification (6 selected papers from 6 submissions). *The workshop and challenges were held virtually.

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.

This two-volume set LNCS 12658 and 12659 constitutes the thoroughly refereed proceedings of the 6th International MICCAI Brainlesion Workshop, BrainLes 2020, the International Multimodal Brain Tumor Segmentation (BraTS) challenge, and the Computational Precision Medicine: Radiology-Pathology Challenge on Brain Tumor Classification (CPM-RadPath) challenge. These were held jointly at the 23rd Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2020, in Lima, Peru, in October 2020.* The revised selected papers presented in these volumes were organized in the following topical sections: brain lesion image analysis (16 selected papers from 21 submissions); brain tumor image segmentation (69 selected papers from 75 submissions); and computational precision medicine: radiology-pathology challenge on brain tumor classification (6 selected papers from 6 submissions). *The workshop and challenges were held virtually.

This must-have text provides an insight into the science behind radiographic technology. Suitable for radiography and radiology students at all levels, the text uses illustrations and simple analogies to explain the fundamentals, while retaining more complex concepts for those with a more advanced knowledge of radiological physics. Updated by authors Martin Vosper, Andrew England and Victoria Major to reflect advances and key topics in medical imaging practice, this text will support radiographers in their core role of obtaining high quality images and optimal treatment outcomes. Strong links between theory and practice throughout, with updated clinical scenarios Clear and concise text featuring insight boxes and summary points More than 60 new diagrams Logically organised to match the order of delivery used in current teaching programmes Updated to reflect advances in medical imaging practice and changes to teaching curricula New information on X-ray exposure factors and their effect on the radiographic image; non-ionising radiation safety - MRI, ultrasound; mobile, portable and dental systems; multimodality imaging, registration and fusion; and the science of body tissue depiction; and PACS technology Enhanced focus on diagnostic imaging Evolve resources to support learning and teaching

This book constitutes the refereed proceedings of the Third International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2020, and the Second International Workshop on Radiogenomics in Neuro-oncology, RNO-AI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020.*For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging. For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience. *The workshops were held virtually due to the COVID-19 pandemic.

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.

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.

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.