This volume presents current advanced technologies and methods used in super-resolution microscopy. The chapters in this book cover a wide range of topics such as introducing super-resolution microscopy into a core facility; two-photon STED microscopy for nanoscale imaging of neural morphology in vivo; correlative SIM-STORM microscopy; two-color single-molecule tracking in live cells; and correlative single molecule localization microscopy and confocal microscopy. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Super-Resolution Microscopy: Methods and Protocols is a valuable resource for both established and novel researchers and users in this field.

This volume covers state-of-the-art applications of solid-state and solution nuclear magnetic resonance( NMR) spectroscopy to study protein structure, dynamics and interactions. Chapters detail various aspects of data acquisition and processing, determination of the structure, multi-timescale dynamics of entities ranging from individual proteins to large macromolecular complexes to intact viral assemblies. The final two chapters will highlight the promise of NMR beyond field strengths of 1 GHz to study the structure, dynamics and interactions of a larger class of proteins and protein complexes of extraordinary biological interest. Written in the highly successful Methods in Molecular Biology series format, chapters provide detailed laboratory protocols and troubleshooting tips that would be of great practical help to NMR spectroscopists with different levels of expertise. Authoritative and cutting-edge, Protein NMR: Methods and Protocol aims to ensure successful results in the further study of this vital field.

This book describes the molecular mechanisms of lung cancer development and progression that determine therapeutic interventions in the era of genomics, when the rapid evolution in lung cancer diagnosis and treatment necessitates critical review of new results to integrate advances into practice. The text opens with background and emerging information regarding the molecular biology of lung cancer pathogenesis. Updated results regarding lung cancer prevention and screening are discussed, followed by chapters on diagnostic techniques and pathological evaluation. This leads on to a detailed presentation of treatment modalities, from surgery and radiation therapy to standard chemotherapy and targeted agents. The coverage includes resistance to therapy and the emergence of immunotherapy for lung cancer; in addition, the current evidence in respect of small cell lung cancer is summarized. The book presents insights from experts across disciplines to emphasize the importance of collaborative care. Advances in our understanding of issues in geriatric oncology and palliative care complete the comprehensive discussion of lung cancer.

This book explores the non-interventional aspects of interventional pulmonology, focusing on diseases of the central airways. As the field of bronchology and interventional pulmonology expands, newer conditions involving the central airways are being recognized with increasing frequency. Current literature has mainly focused on technical aspects of the subspecialty, but this book illuminates what else interventional pulmonology has to offer the pulmonologist, including diagnosis and alternate therapeutic options. Diseases of the Central Airways: A Clinical Guide presents techniques for the diagnoses, management and treatment of patients with intriguing central airway conditions such as: black bronchoscopy, tracheobronchomalacia, endobronchial tuberculosis, and tracheobronchopathia osteochondroplastica. In-depth chapters are written by international experts and are up-to-date and comprehensive reviews. This important new book will contribute significantly to the welfare of patients with lung ailments of the central airways.

This book constitutes revised selected papers from the Third International MICCAI Brainlesion Workshop, BrainLes 2017, as well as the International Multimodal Brain Tumor Segmentation, BraTS, and White Matter Hyperintensities, WMH, segmentation challenges, which were held jointly at the Medical Image computing for Computer Assisted Intervention Conference, MICCAI, in Quebec City, Canada, in September 2017. The 40 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections named: brain lesion image analysis; brain tumor image segmentation; and ischemic stroke lesion image segmentation.

This book constitutes the refereed joint proceedings of the International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, the International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017, and the International Stroke Workshop: Imaging and Treatment Challenges, SWITCH 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 5 full papers presented at FIFI 2017, the 9 full papers presented at RAMBO 2017, and the 4 full papers presented at SWITCH 2017 were carefully reviewed and selected. The CMMI papers cover various areas from image synthesis to data analysis and from clinical diagnosis to therapy individualization, using molecular imaging modalities PET, SPECT, PET/CT, SPECT/CT, and PET/MR. The RAMBO papers present research from both academia and industry, They are organized into the categories "registration and tracking" and "image reconstruction and information retrieval" while application areas include cardiac, pulmonal, abdominal, fetal, and renal imaging. The SWITCH papers focus on CT(A)-based quantitative imaging biomarkers for stroke.

This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.

The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.

The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.

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.

This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis.

The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.

This book highlights the experimental investigations that have been carried out on magnetic resonance imaging and computed tomography (MRI & CT) images using state-of-the-art Computational Image processing techniques, and tabulates the statistical values wherever necessary. In a very simple and straightforward way, it explains how image processing methods are used to improve the quality of medical images and facilitate analysis. It offers a valuable resource for researchers, engineers, medical doctors and bioinformatics experts alike.

This book constitutes the refereed proceedings of the Second International Workshop on Simulation and Synthesis in Medical Imaging, held in conjunction with MICCAI 2017, in Quebec City, Canada, in September 2017. The 11 revised full papers presented were carefully reviewed and selected from 14 submissions. The contributions span the following broad categories: cross modality (PET/MR, PET/CT, CT/MR, etc.) image synthesis, simulation and synthesis from large-scale image databases, automated techniques for quality assessment images, and several applications of image synthesis and simulation in medical imaging such as image interpolation and segmentation, image reconstruction, cell imaging, and blood flow.

This book constitutes the refereed proceedings of the Third International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2017, which was held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 18 regular papers presented in this volume were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections on multi-atlas segmentation; segmentation; Alzheimer's disease; reconstruction, denoising, super-resolution; tumor, lesion; and classification, retrival.

Prepare for success on the musculoskeletal imaging component of the radiology Core Exam! Musculoskeletal Imaging: A Core Review, Second Edition, is an up-to-date, practical review tool written specifically for the Core Exam. This helpful resource contains 300 image-rich, multiple-choice questions with detailed explanations of right and wrong answers, fully revised content, high-yield tables for easy review, and additional eBook questions to ensure you're ready for the Core Exam or recertification exam. Features questions in all exam areas, including imaging basics, normal anatomy, congenital and developmental spine/extremity anomalies and dysplasias, infection, tumors and tumor-like conditions, trauma, metabolic and hematologic disorders, arthropathy, and more. Accompanies each question with 1 or 2 high-quality radiographs, CT, MR, or ultrasound images. Provides concise answers with explanations of each choice followed by relevant, up-to-date references. Follows the structure and content of what you'll encounter on the test, conveniently organized by topic. 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.

Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis.

This book serves as a practical guide for the use of stereotactic body radiation therapy in clinics. On the basis of more than 10 years of clinical experience with lung cancer, liver cancer and other cancers, a remarkable volume of knowledge has been accumulated. At the same time, great progress in techniques has been achieved. Various new fixing apparatuses, new respiratory regulation techniques, new dose fractionation schedules and new image-guided radiation therapy machines have been developed. This book reviews the history of those developments and reports on various types of toxicities. Review of recent clinical studies is also included. The authors were key members of the JCOG 0403 clinical trials on stereotactic body radiation therapy (SBRT) for both inoperable and operableT1N0M0 primary lung cancer. Readers will learn of the superior outcomes obtained with SBRT for lung cancer and other cancers in terms of local control and toxicities. With its practical focus, this book will benefit radiation oncologists, medical physicists, medical dosimetrists, radiation therapists and senior nurses as well as medical oncologists and surgical oncologists who are interested in radiotherapy.

This book constitutes the revised selected papers from the 5th International Workshop on Clinical Image-Based Procedures, CLIP 2016, held in conjunction with MICCAI 2016 in Athens, Greece, in October 2016. The 10 papers presented in this volume were carefully reviewed and selected from 16 submissions. Specific topics include various image segmentation and registration techniques, applied to various parts of the body. They range from interventional planning to navigation of devices and navigation to the anatomy of interest. Clinical applications cover the skull, the cochlea, cranial nerves, the aortic valve, wrists, and the abdomen, among others.

While specialists often guide the care to lung cancer patients, it is often a general radiologist who is left to interpret studies that impact patient care and management. Lung Cancer Imaging provides a comprehensive guide to the diagnosis, staging and overview of the management of lung cancer relevant to practicing radiologists so that they can better understand the decision making issues and provide more directed and useful communication to the treating physicians. It Primary Care physicians will also find this book valuable to understand the relevant issues that they face when one of their patients is being treated for lung cancer.

The horizons of sophisticated imaging have expanded with the use of combined positron emission tomography (PET) and computed tomography (CT). PET-CT has revolutionized medical imaging by adding anatomic localization to functional imaging, thus providing physicians with information that is vital for the accurate diagnosis and treatment of pathologies. Since the integration of PET and CT several years ago, PET/CT procedures are now routine at leading medical centers throughout the world. This has increased the importance of nuclear medicine physicians acquiring a broad knowledge in sectional anatomy for image interpretation. The Atlas of Sectional Radiological Anatomy for PET/CT is a user-friendly guide presenting high-resolution, full-color images of anatomical detail and focuses solely on normal FDG distribution throughout the head & neck, thorax, abdomen, and pelvis, the primary sites for cancer detection and treatment through PET/CT.

This practical, up-to-date, bedside-oriented radiation oncology book encompasses the essential aspects of the subject with coverage on radiation physics, radiobiology, and clinical radiation oncology. The first two sections examine concepts that are crucial in radiation physics and radiobiology. The third section describes radiation treatment regimens appropriate for the main cancer sites and tumor types.

Measurement of solid tumor response to treatment relies mainly on imaging. WHO tumor response criteria and, more recently, RECIST (response evaluation criteria in solid tumors) have provided means to objectively measure tumor response in clinical trials with imaging. These guidelines have been rapidly adopted in clinical practice to monitor patient treatment and for therapy planning. However, relying only on anatomical information is not always sufficient when evaluating new drugs that will reduce a tumor's functionality while preserving its size. Finding more reliable and reproducible measures of tumor response is one of the most important and difficult challenges facing modern radiology as it requires an entirely new approach to imaging. The aim of this book is to address the assessment of response to treatment by adopting a multidisciplinary perspective, just as occurs in real life in a comprehensive cancer center. Oncologists and imaging experts consider two cancer models, locally advanced disease and metastatic disease, jointly exploring both conventional and advanced means of measuring response to standard treatment protocols and new targeted therapies.

This new up-to-date edition of the successful handbook and ready reference retains the proven concept of the first, covering basic and advanced methods and applications in infrared imaging from two leading expert authors in the field. All chapters have been completely revised and expanded and a new chapter has been added to reflect recent developments in the field and report on the progress made within the last decade. In addition there is now an even stronger focus on real-life examples, with 20% more case studies taken from science and industry. For ease of comprehension the text is backed by more than 590 images which include graphic visualizations and more than 300 infrared thermography figures. The latter include many new ones depicting, for example, spectacular views of phenomena in nature, sports, and daily life.

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.