Computational Anatomy Based On Whole Body Imaging
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Computational Anatomy Based On Whole Body Imaging
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Author : Hidefumi Kobatake
language : en
Publisher: Springer
Release Date : 2017-06-14
Computational Anatomy Based On Whole Body Imaging written by Hidefumi Kobatake and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-14 with Technology & Engineering categories.
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.
Multidisciplinary Computational Anatomy
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Author : Makoto Hashizume
language : en
Publisher: Springer Nature
Release Date : 2021-11-30
Multidisciplinary Computational Anatomy written by Makoto Hashizume and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-30 with Medical categories.
This volume thoroughly describes the fundamentals of a new multidisciplinary field of study that aims to deepen our understanding of the human body by combining medical image processing, mathematical analysis, and artificial intelligence. Multidisciplinary Computational Anatomy (MCA) offers an advanced diagnosis and therapeutic navigation system to help detect or predict human health problems from the micro-level to macro-level using a four-dimensional, dynamic approach to human anatomy: space, time, function, and pathology. Applying this dynamic and “living” approach in the clinical setting will promote better planning for – and more accurate, effective, and safe implementation of – medical management. Multidisciplinary Computational Anatomy will appeal not only to clinicians but also to a wide readership in various scientific fields such as basic science, engineering, image processing, and biomedical engineering. All chapters were written by respected specialists and feature abundant color illustrations. Moreover, the findings presented here share new insights into unresolved issues in the diagnosis and treatment of disease, and into the healthy human body.
Intelligent Orthopaedics
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Author : Guoyan Zheng
language : en
Publisher: Springer
Release Date : 2018-10-10
Intelligent Orthopaedics written by Guoyan Zheng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-10 with Medical categories.
This book introduces readers to the latest technological advances in the emerging field of intelligent orthopaedics. Artificial intelligence and smart instrumentation techniques are now revolutionizing every area of our lives, including medicine. The applications of these techniques in orthopaedic interventions offer a number of potential benefits, e.g. reduced incision size and scarring, minimized soft tissue damage, and decreased risk of misalignment. Consequently, these techniques have become indispensable for various orthopaedic interventions, which has led to the emerging field of intelligent orthopaedics. Addressing key technologies and applications, this book offers a valuable guide for all researchers and clinicians who need an update on both the principles and practice of intelligent orthopaedics, and for graduate students embarking on a career in this field.
Computational Methods Of Modeling Vascular Geometry And Tracking Pulmonary Motion From Medical Images
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Author : Guanglei Xiong
language : en
Publisher: Stanford University
Release Date : 2011
Computational Methods Of Modeling Vascular Geometry And Tracking Pulmonary Motion From Medical Images written by Guanglei Xiong and has been published by Stanford University this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Modern anatomical medical imaging technologies, such as computed tomography and magnetic resonance, capture structures of the human body in exquisite detail. Computational anatomy is a developing discipline to extract and characterize the anatomy from images. Unfortunately, anatomical images do not reveal the functional behavior. Computational physiology shows great potential to link the structure-function relationship by considering both the anatomical information and the physical governing laws. The simulated physiology can be used to assess physiological states, and more importantly predict the outcomes of interventions. On the other hand, advances in the functional imaging techniques provide measured physiology information and should be utilized together with computational physiology. In the theme of computational anatomy and physiology, this dissertation describes computational methods of modeling vascular geometry for image-based blood flow computation and tracking pulmonary motion for image-guided radiation therapy. Blood flow computation is a useful tool to quantify in vivo hemodynamics. The essential first step is to model vascular geometry from medical imaging data. I have developed a new workflow for this task. The geometric model construction is based on 3D image segmentation and geometric processing. To represent the topology of the constructed model, I have developed a novel centerline extraction method. To account for compliant vessels, methods to assign spatially-varying mechanical properties of the vessel wall are also developed. The workflow greatly increases the modeling efficiency. The combination of the patient-specific geometry and wall deformation can enhance the fidelity of blood flow simulation. Image-based blood flow computation also holds great promise for device design and surgical procedure evaluation. Next, I have developed novel virtual intervention methods to deploy stents or stent grafts to patient-specific pre-operative geometric models constructed from medical images. These methods enable prospective model construction and may be used to evaluate the outcomes of alternative treatment options. Respiratory motion is closely related to the physiology of the lung. Finally, I have developed a novel framework to track patient-specific pulmonary motion from 4D computed tomography images. A large set of vascular junction structures in the lung are identified as landmarks and tracked to obtain their motion trajectories. This framework can provide accurate motion information, which is important in radiation therapy to reduce healthy tissue irradiation while allowing target dose escalation. This work demonstrates the importance of the geometry and motion modeling tools in computational anatomy and physiology. Accurate physiological information, whether simulated or measured, will benefit the diagnosis and treatment of various diseases.
Medical Imaging Systems Technology Methods In General Anatomy
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Author : Cornelius T. Leondes
language : en
Publisher: World Scientific
Release Date : 2005
Medical Imaging Systems Technology Methods In General Anatomy written by Cornelius T. Leondes and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Medical categories.
This scholarly set of well-harmonized volumes provides indispensable and complete coverage of the exciting and evolving subject of medical imaging systems. Leading experts on the international scene tackle the latest cutting-edge techniques and technologies in an in-depth but eminently clear and readable approach.Complementing and intersecting one another, each volume offers a comprehensive treatment of substantive importance to the subject areas. The chapters, in turn, address topics in a self-contained manner with authoritative introductions, useful summaries, and detailed reference lists. Extensively well-illustrated with figures throughout, the five volumes as a whole achieve a unique depth and breath of coverage.As a cohesive whole or independent of one another, the volumes may be acquired as a set or individually.
Building Computational Atlases From Databases Of Whole Body Clinical Pet
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Author : Vaclav Potesil
language : en
Publisher:
Release Date : 2011
Building Computational Atlases From Databases Of Whole Body Clinical Pet written by Vaclav Potesil and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Medical imaging has revolutionized cancer care and its use has grown massively over the past several decades. Images are increasingly stored in large digital image repositories such as hospital Picture Archiving and Communication System, which will hopefully provide a wealth of information on patient conditions and therapy outcomes as cancer diagnosis and therapy moves from 'one size fits all' to more personalized approaches tailored to each particular patient. However, converting the unstructured avalanche of data at thousands of different hospitals into clinically valuable biomarkers and tools requires that the images of different patients can be compared and efficiently searched. Our research aims to develop novel methods to compare whole-body scans of multiple patients; methods which incorporate 'intelligent' prior knowledge of the internal structure of the human body, as opposed to current methods of image registration which mostly rely on matching the voxel intensities and disregard their anatomical meaning. We develop computational methods for accurate and reliable automated localization of anatomical structures in whole-body images, which will help to automate key steps in cancer diagnosis and radiation treatment planning and save expensive clinicians' time while improving the reliability of their decisions. Conventional approaches to determining spatial correspondences between pairs or sets of images in medical imaging typically rely on image registration methods. There have been considerable advances in registration of multiple images of the same patient taken at different time-points, known as longitudinal studies. However, conventional methods, which rely on optimizing certain integral functions of voxel values over the entire image, are unreliable when applied to aligning whole-body images of different patients. Whole-body Computed Tomography (CT) images contain many different anatomical structures whose physical attributes and consequent appearance can be highly variable between patients. This substantial, but normal, variability is further increased by the presence of pathologies such as tumours and non-cancerous diseases, surgical interventions and degenerative changes due to aging as well as different patterns of contrast agent uptake. Conventional registration methods often get trapped in local minima that abound in such images, resulting in unreliable and inaccurate anatomical correspondences. The methods developed in this thesis tackle the problem of inter-patient registration by incorporating prior anatomical knowledge into parts-based graphical models that accurately and reliably localize arbitrary skeletal and soft-tissue anatomical landmarks in whole-body clinical oncology scans. We optimize parts-based graphical models called Pictorial Structures for accurate and reliable landmark localization in CT images and introduce novel methods that replace standard population models by models personalized to the particular patient. We also propose methods that further improve landmark localization while minimizing, as far as possible, the high costs of ground-truth annotation by expert radiologists. We do this by automatically discovering new landmark correspondences from a database of partially annotated images. The performance of the algorithms developed in my thesis is evaluated on a large database of clinical lung cancer PET/CT scans, showing superior accuracy and reliability of landmark localization compared to conventional methods.
Handbook Of Anatomical Models For Radiation Dosimetry
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Author : Xie George Xu
language : en
Publisher: CRC Press
Release Date : 2009-09-01
Handbook Of Anatomical Models For Radiation Dosimetry written by Xie George Xu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-01 with Medical categories.
Over the past few decades, the radiological science community has developed and applied numerous models of the human body for radiation protection, diagnostic imaging, and nuclear medicine therapy. The Handbook of Anatomical Models for Radiation Dosimetry provides a comprehensive review of the development and application of these computational mode
Cases On Virtual Reality Modeling In Healthcare
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Author : Tang, Yuk Ming
language : en
Publisher: IGI Global
Release Date : 2021-12-17
Cases On Virtual Reality Modeling In Healthcare written by Tang, Yuk Ming and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-17 with Computers categories.
Virtual reality (VR) provides immersive stereoscopic visualization of virtual environments, and the visualization effect and computer graphics are critical to enhancing the engagement of participants and achieving optimal education and training effectiveness. Constructing realistic 3D models and scenarios for a specific application of VR simulation is no easy task. There are many different tools for 3D modeling. However, many of the modeling tools are used for manufacturing and product design applications and have advanced features and functions which may not be applicable to different levels of users and various specializations. Cases on Virtual Reality Modeling in Healthcare introduces the use of Blender for VR 3D modeling, demonstrates healthcare applications, and examines potential uses in modeling, dressing, and animation in healthcare. Covering a range of topics such as cross reality, rehabilitation games, and augmented reality, this book is ideal for engineers, industry professionals, practitioners, researchers, academicians, instructors, and students.
Computational Methods Of Modeling Vascular Geometry And Tracking Pulmonary Motion From Medical Images
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Author : Guanglei Xiong
language : en
Publisher:
Release Date : 2011
Computational Methods Of Modeling Vascular Geometry And Tracking Pulmonary Motion From Medical Images written by Guanglei Xiong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Modern anatomical medical imaging technologies, such as computed tomography and magnetic resonance, capture structures of the human body in exquisite detail. Computational anatomy is a developing discipline to extract and characterize the anatomy from images. Unfortunately, anatomical images do not reveal the functional behavior. Computational physiology shows great potential to link the structure-function relationship by considering both the anatomical information and the physical governing laws. The simulated physiology can be used to assess physiological states, and more importantly predict the outcomes of interventions. On the other hand, advances in the functional imaging techniques provide measured physiology information and should be utilized together with computational physiology. In the theme of computational anatomy and physiology, this dissertation describes computational methods of modeling vascular geometry for image-based blood flow computation and tracking pulmonary motion for image-guided radiation therapy. Blood flow computation is a useful tool to quantify in vivo hemodynamics. The essential first step is to model vascular geometry from medical imaging data. I have developed a new workflow for this task. The geometric model construction is based on 3D image segmentation and geometric processing. To represent the topology of the constructed model, I have developed a novel centerline extraction method. To account for compliant vessels, methods to assign spatially-varying mechanical properties of the vessel wall are also developed. The workflow greatly increases the modeling efficiency. The combination of the patient-specific geometry and wall deformation can enhance the fidelity of blood flow simulation. Image-based blood flow computation also holds great promise for device design and surgical procedure evaluation. Next, I have developed novel virtual intervention methods to deploy stents or stent grafts to patient-specific pre-operative geometric models constructed from medical images. These methods enable prospective model construction and may be used to evaluate the outcomes of alternative treatment options. Respiratory motion is closely related to the physiology of the lung. Finally, I have developed a novel framework to track patient-specific pulmonary motion from 4D computed tomography images. A large set of vascular junction structures in the lung are identified as landmarks and tracked to obtain their motion trajectories. This framework can provide accurate motion information, which is important in radiation therapy to reduce healthy tissue irradiation while allowing target dose escalation. This work demonstrates the importance of the geometry and motion modeling tools in computational anatomy and physiology. Accurate physiological information, whether simulated or measured, will benefit the diagnosis and treatment of various diseases.
Deep Learning In Medical Image Analysis
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Author : Gobert Lee
language : en
Publisher: Springer Nature
Release Date : 2020-02-06
Deep Learning In Medical Image Analysis written by Gobert Lee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-06 with Medical categories.
This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.