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 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 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 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 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.

Interpret the complexities of neuroanatomy like never before with the unparalleled coverage and expert guidance from Drs. Srinivasan Mukundan and Thomas C. Lee in this outstanding volume of the Netter's Correlative Imaging series. Beautiful and instructive Netter paintings and illustrated cross-sections created in the Netter style are presented side by side high-quality patient images and key anatomic descriptions to help you envision and review intricate neuroanatomy. View the brain, spinal cord, and cranial nerves, as well as head and neck anatomy through modern imaging techniques in a variety of planes, complemented with a detailed illustration of each slice done in the instructional and aesthetic Netter style. Find anatomical landmarks quickly and easily through comprehensive labeling and concise text highlighting key points related to the illustration and image pairings. Correlate patient data to idealized normal anatomy, always in the same view with the same labeling system. Access NetterReference.com where you can quickly and simultaneously scroll through images and illustrations.

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 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.

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.

A comprehensive, systemically organised 'film viewing' book designed specifically for FRCR candidates but equally useful to all trainee and junior radiologists as an 'aide memoire' and to medical undergraduates and MRCP candidates as a useful means of self-testing their level of knowledge. It is fully illustrated with high-quality, clearly labeled black and white illustrations throughout and the text closely mirrors the way that questions are asked in the FRCR film viewing examination, so as to provide as real an examination experience as possible. Each section of the book contains 20 representative questions, and model answers, providing 200 cases altogether. First published in 2000.

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.

This book constitutes the First Cerebral Aneurysm Detection Challenge, CADA 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in October 2020. The conference was planned to take place in Lima, Peru, and took place virtually due to the COVID-19 pandemic. The 9 regular papers presented in this volume, together with an overview and one introduction paper, were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: cerebral aneurysm detection; cerebral aneurysm segmentation; and cerebral aneurysm rupture risk estimation.

This book constitutes the proceedings of the 7th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2019, which was held in conjunction with MICCAI on October 17, 2019, in Shenzhen, China. All submissions were accepted for publication; the book contains 5 peer-reviewed regular papers, covering topics of vertrebra detection, spine segmentation and image-based diagnosis, and 9 challenge papers, investigating (semi-)automatic spinal curvature estimation algorithms and providing a standard evaluation framework with a set of x-ray images.

Develop a working knowledge of radiologic science as it applies to producing diagnostic-quality images - and prepare for the Veterinary Technology National Exam (VTNE) - with Lavin's Radiography for Veterinary Technicians, 7th Edition! Written in a way that is easy to follow and understand, all aspects of imaging, including production, positioning, and evaluation of radiographs, are covered in this comprehensive text. All chapters have been thoroughly reviewed, revised, and updated with vivid color equipment photos, positioning drawings, and detailed anatomy drawings. From foundational concepts to the latest in diagnostic imaging, this text is a valuable resource for students, technicians, and veterinarians alike! Comprehensive content explores the physics of radiography, the equipment, the origin of film artifacts, and positioning and restraint of small, large, avian, and exotic animals. More than 1,000 full-color photos and updated radiographic images visually demonstrate the relationship between anatomy and positioning. UNIQUE! Coverage of non-manual restraint techniques, including sandbags, tape, rope, sponges, sedation, and combinations, improve safety and enhance radiation protection. Emphasis on digital imaging, including quality factors and post-processing, keeps you up to date on the most recent developments in digital technology. UNIQUE! Dental radiography chapter covers equipment types (film, digital, and computed radiography), safety, positioning, and reading the image for the dog and cat to address the needs of both general and specialty veterinary technicians. Broad coverage of radiologic science, physics, imaging, and protection provides you with the foundation needed to develop good imaging practices and techniques. NEW! Coverage of the latest protocols ensures all-inclusive coverage.

The three-volume set LNCS 6891, 6892 and 6893 constitutes the refereed proceedings of the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011, held in Toronto, Canada, in September 2011. Based on rigorous peer reviews, the program committee carefully selected 251 revised papers from 819 submissions for presentation in three volumes. The second volume includes 83 papers organized in topical sections on diffusion weighted imaging, fMRI, statistical analysis and shape modeling, and registration.