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This book constitutes the refereed proceedings of the International Workshop CCAAI 2012, held in Nice, France, in October 2012. The book includes 31 papers which were carefully reviewed and selected from 37 submissions. All of the accepted papers were revised by incorporating of the reviewers’ comments and re-submitted by the authors to be included in this proceedings volume. The papers are organized into topical sections on colon and other gastrointestinal tract; and liver, kidney, and other organs.
This book constitutes the refereed proceedings of the 6th International Workshop ABDI 2014, held in conjunction with MICCAI 2014, in Cambridge, MA, USA, in September 2014. The book includes 29 papers which were carefully reviewed and selected from 33 submissions. The topics covered are liver and pancreas - ablation, perfusion, and segmentation; gastrointestinal tract - Crohn's disease; gastrointestinal tract - colonoscopy, colonography; and abdominal operation planning - registration, segmentation.
This book constitutes the refereed proceedings of the 5th International Workshop CCAA 2013, held in conjunction with MICCAI 2013, in Nagoya, Japan, in September 2013. The book includes 32 papers which were carefully reviewed and selected from 38 submissions. The topics covered are abdominal atlases, shape analysis and morphology in abdominal structures and organs, detection of anatomical and functional landmarks, dynamic, functional, physiologic, and anatomical abdominal imaging, registration methods for abdominal intra- and inter-patient variability, augmented reality techniques for intervention, clinical applications in radio-frequency ablation, open surgery, and minimally invasive surgery.
This book deals with computational anatomy, an emerging discipline recognized in medical science as a derivative of conventional anatomy. It is also a completely new research area on the boundaries of several sciences and technologies, such as medical imaging, computer vision, and applied mathematics. Computational Anatomy Based on Whole Body Imaging highlights the underlying principles, basic theories, and fundamental techniques in computational anatomy, which are derived from conventional anatomy, medical imaging, computer vision, and applied mathematics, in addition to various examples of applications in clinical data. The book will cover topics on the basics and applications of the new discipline. Drawing from areas in multidisciplinary fields, it provides comprehensive, integrated coverage of innovative approaches to computational anatomy. As well, Computational Anatomy Based on Whole Body Imaging serves as a valuable resource for researchers including graduate students in the field and a connection with the innovative approaches that are discussed. Each chapter has been supplemented with concrete examples of images and illustrations to facilitate understanding even for readers unfamiliar with computational anatomy.
This volume comprises of 21 selected chapters, including two overview chapters devoted to abdominal imaging in clinical applications supported computer aided diagnosis approaches as well as different techniques for solving the pectoral muscle extraction problem in the preprocessing part of the CAD systems for detecting breast cancer in its early stage using digital mammograms. The aim of this book is to stimulate further research in medical imaging applications based algorithmic and computer based approaches and utilize them in real-world clinical applications. The book is divided into four parts, Part-I: Clinical Applications of Medical Imaging, Part-II: Classification and clustering, Part-III: Computer Aided Diagnosis (CAD) Tools and Case Studies and Part-IV: Bio-inspiring based Computer Aided diagnosis techniques.
This book constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Computational Challenges and Clinical Opportunities in Virtual Colonoscopy and Abdominal Imaging, held in conjunction with MICCAI 2010, in Beijing, China, on September 20, 2010. The 19 revised full papers presented were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections on CT colonography CAD, abdominal imaging, and virtual colonoscopy.
Computational Intelligence in Biomedical Imaging is a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients’ medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians’ decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy.
The book covers novel strategies of state of the art in engineering and clinical analysis and approaches for analyzing abdominal imaging, including lung, mediastinum, pleura, liver, kidney and gallbladder. In the last years the imaging techniques have experienced a tremendous improvement in the diagnosis and characterization of the pathologies that affect abdominal organs. In particular, the introduction of extremely fast CT scanners and high Magnetic field MR Systems allow imaging with an exquisite level of detail the anatomy and pathology of liver, kidney, pancreas, gallbladder as well as lung and mediastinum. Moreover, thanks to the development of powerful computer hardware and advanced mathematical algorithms the quantitative and automated\semi automated diagnosis of the pathology is becoming a reality. Medical image analysis plays an essential role in the medical imaging field, including computer-aided diagnosis, organ/lesion segmentation, image registration, and image-guided therapy. This book will cover all the imaging techniques, potential for applying such imaging clinically, and offer present and future applications as applied to the abdomen and thoracic imaging with the most world renowned scientists in these fields. The main aim of this book is to help advance scientific research within the broad field of abdominal imaging. This book focuses on major trends and challenges in this area, and it presents work aimed to identify new techniques and their use in medical imaging analysis for abdominal imaging. ​
This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
The three-volume set LNCS 9900, 9901, and 9902 constitutes the refereed proceedings of the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, held in Athens, Greece, in October 2016. Based on rigorous peer reviews, the program committee carefully selected 228 revised regular papers from 756 submissions for presentation in three volumes. The papers have been organized in the following topical sections: Part I: brain analysis, brain analysis - connectivity; brain analysis - cortical morphology; Alzheimer disease; surgical guidance and tracking; computer aided interventions; ultrasound image analysis; cancer image analysis; Part II: machine learning and feature selection; deep learning in medical imaging; applications of machine learning; segmentation; cell image analysis; Part III: registration and deformation estimation; shape modeling; cardiac and vascular image analysis; image reconstruction; and MR image analysis.