Download or read book Prediction of Respiratory Motion for Radiotherapy Applications written by Asad Rasheed and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy written by Jan Ehrhardt and published by Springer Science & Business Media. This book was released on 2013-05-30 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Respiratory motion causes an important uncertainty in radiotherapy planning of the thorax and upper abdomen. The main objective of radiation therapy is to eradicate or shrink tumor cells without damaging the surrounding tissue by delivering a high radiation dose to the tumor region and a dose as low as possible to healthy organ tissues. Meeting this demand remains a challenge especially in case of lung tumors due to breathing-induced tumor and organ motion where motion amplitudes can measure up to several centimeters. Therefore, modeling of respiratory motion has become increasingly important in radiation therapy. With 4D imaging techniques spatiotemporal image sequences can be acquired to investigate dynamic processes in the patient’s body. Furthermore, image registration enables the estimation of the breathing-induced motion and the description of the temporal change in position and shape of the structures of interest by establishing the correspondence between images acquired at different phases of the breathing cycle. In radiation therapy these motion estimations are used to define accurate treatment margins, e.g. to calculate dose distributions and to develop prediction models for gated or robotic radiotherapy. In this book, the increasing role of image registration and motion estimation algorithms for the interpretation of complex 4D medical image sequences is illustrated. Different 4D CT image acquisition techniques and conceptually different motion estimation algorithms are presented. The clinical relevance is demonstrated by means of example applications which are related to the radiation therapy of thoracic and abdominal tumors. The state of the art and perspectives are shown by an insight into the current field of research. The book is addressed to biomedical engineers, medical physicists, researchers and physicians working in the fields of medical image analysis, radiology and radiation therapy.
Download or read book Prediction of Respiratory Motion written by Suk Jin Lee and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Radiation therapy is a cancer treatment method that employs high-energy radiation beams to destroy cancer cells by damaging the ability of these cells to reproduce. Thoracic and abdominal tumors may change their positions during respiration by as much as three centimeters during radiation treatment. The prediction of respiratory motion has become an important research area because respiratory motion severely affects precise radiation dose delivery. This study describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. In the first part of our study we review three prediction approaches of respiratory motion, i.e., model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the second part of our work we propose respiratory motion estimation with hybrid implementation of extended Kalman filter. The proposed method uses the recurrent neural network as the role of the predictor and the extended Kalman filter as the role of the corrector. In the third part of our work we further extend our research work to present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. In the fourth part of our work we retrospectively categorize breathing data into several classes and propose a new approach to detect irregular breathing patterns using neural networks. We have evaluated the proposed new algorithm by comparing the prediction overshoot and the tracking estimation value. The experimental results of 448 patients' breathing patterns validated the proposed irregular breathing classifier.
Download or read book Prediction and Classification of Respiratory Motion written by Suk Jin Lee and published by . This book was released on 2013-11-30 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning in Radiation Oncology written by Issam El Naqa and published by Springer. This book was released on 2015-06-19 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Download or read book Adaptive Modelling and Prediction of Respiratory Motion in External Beam Radiotherapy written by Majdi Rashed S. Alnowami and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Respiratory Motion Prediction Based on Time Variant Seasonal Autoregressive Model for Real Time Image Guided Radiotherapy written by Kei Ichiji and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A Respiratory Motion Prediction Based on Time-Variant Seasonal Autoregressive Model for Real-Time Image-Guided Radiotherapy.
Download or read book Respiratory Motion Modeling for Use in Diagnostic Imaging and Radiation Therapy written by Hadi Fayad and published by . This book was released on 2011 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most important parameters reducing the sensitivity and specificity in the thoracic and abdominal areas is respiratory motion and associated deformations which represent today an important challenge in medical imaging. In addition, respiratory motion reduces accuracy in image fusion from combined positron emission tomography computed tomography (PET/CT) systems. Solutions presented to date include respiratory synchronized PET and CT acquisitions. However, differences between acquired 4D PET and corresponding CT image series have been reported due to differences in respiration conditions during PET and CT acquisitions. In addition, the radiation dose burden resulting from a 4D CT acquisition may not be justifiable for every patient. The first objective of this thesis was to generate dynamic CT images from one reference CT image; based on deformation matrices obtained from the elastic registration of 4D non attenuation corrected PET images. Such an approach eliminates, on one hand the need for the acquisition of dynamic CT, while at the same time ensuring the good matching between CT and PET images. The second objective was to develop and evaluate methods of building patient specific respiratory motion models and at as a second step more developed generic respiratory motion models. These models relate the internal motion to the parameters of an external surrogate signal (PET respiratory signal or patient's surface) that can be acquired during data acquisition and treatment delivery. Finally, the two developed models were validated and used in the PET respiratory motion and attenuation correction and in radiation therapy applications.
Download or read book Interdisciplinary Approaches for 4D Radiotherapy of Moving Lung Tumors Based on Nonlinear Dynamics Systems Theory written by and published by . This book was released on 2012 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intra-fractional tumor motion mainly due to respiratory motion necessitates enlarged treatment margins to provide full tumor coverage, thus limiting the dose that can be escalated for tumor control. Tumor motion and breathing irregularity are two major hurdles which stop us from achieving this apparently simple goal of dose escalation while sparing normal tissues. Delivery of radiation therapy using synchronization methodologies requires knowledge of real-time tumor position. All methodologies suffer from the problem of system latency which can be understood as a delay from the instant the tumor moves before the treatment system can make its corrective response. Predicting respiratory motion in real-time is challenging, due to the inherent chaotic nature of breathing patterns, i.e. sensitive dependence on initial conditions. In our previous work we established that respiratory system is 5-6 dimensional nonlinear, stationary and deterministic in nature albeit chaotic with sensitive dependence to initial conditions. In this thesis, we introduce nonlinear prediction algorithms based on state-space methodologies that have a larger prediction horizon than linear methods, A much larger prediction horizon can be achieved if patients can be coached to closely follow a regular breathing pattern. Patients revisit their breathing orbits arbitrarily closely and stay for a while before exponentially diverging from the orbit. These are called Unstable Periodic Orbits (UPOs) which can be used to intelligently coach the patients to maintain a comfortable breathing. This approach is called Chaos Control and its theoretical basis and preliminary results are elucidated in this thesis. However, many patients with high transients can be very challenging for both prediction and chaos control. We introduce a novel method, Recurrence quantification analysis (RQA) to classify patients breathing pattern to decide if a patient is a good candidate for Chaos control and prediction or just prediction bundled with 4D treatment.
Download or read book Stationary and Non stationary Time Series Prediction Using State Space Model and Pattern based Approach written by Kin Ming Kam and published by . This book was released on 2015 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: The motion-adaptive radiotherapy techniques are promising to deliver ablative radiation doses to tumor with minimal normal tissue exposure by accounting for real-time tumor movement. However, a major challenge of successful applications of these techniques is the real-time prediction of target motion to accommodate system delivery latencies. Predicting respiratory motion in real-time is challenging. The current respiratory motion prediction approaches are still not satisfactory in terms of accuracy and interpretability. Therefore, we propose a novel respiratory motion prediction approach based on future values of best-matching patterns. In particular, there are three major ingredients of this approach: (1) construct a real-time accumulated pattern library by orthogonal polynomial approximation using a sliding window approach, (2) find k nearest-neighbor patterns in the pattern library and apply a twostep approach to screen out the disturbing patterns and find out the final predictive patterns. (3) the final prediction is made using the bootstrapped mean of the future values of the selected predictive patterns given a prediction horizon. Based on a study of respiratory motion traces of 27 patients with lung cancer, the proposed prediction approach has generated consistently signicant higher accuracies than the current respiratory motion prediction approaches, particularly for long prediction lengths. There has been much interest in the beneficial effects of musical training on cognition. Previous studies have indicated that musical training was related to better working memory and that these behavioral differences were associated with differences in neural activity in the brain. However, it was not clear whether musical training impacts memory in general, beyond working memory. A comprehensive EEG pattern study has been performed, including various univariate and multivariate features, time-frequency (wavelet) analysis, power-spectra analysis, and deterministic chaotic theory. The advanced feature selection approaches have also been employed to select the most discriminative EEG and brain activation features between musicians and non-musicians. High classification accuracy (more than 95%) in memory judgments was achieved using Proximal Support Vector Machine (PSVM). For working memory, it showed significant differences between musicians versus non-musicians during the delay period. For long-term memory, significant differences on EEG patterns between groups were found both in the pre-stimulus period and the post-stimulus period on recognition. These results indicate that musicians memorial advantage occurs in both working memory and long-term memory and that the developed computational framework using advanced data mining techniques can be successfully applied to classify complex human cognition with high time resolution.
Download or read book Surface Guided Radiation Therapy written by Jeremy David Page Hoisak and published by CRC Press. This book was released on 2020-02-13 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surface Guided Radiation Therapy provides a comprehensive overview of optical surface image guidance systems for radiation therapy. It serves as an introductory teaching resource for students and trainees, and a valuable reference for medical physicists, physicians, radiation therapists, and administrators who wish to incorporate surface guided radiation therapy (SGRT) into their clinical practice. This is the first book dedicated to the principles and practice of SGRT, featuring: Chapters authored by an internationally represented list of physicists, radiation oncologists and therapists, edited by pioneers and experts in SGRT Covering the evolution of localization systems and their role in quality and safety, current SGRT systems, practical guides to commissioning and quality assurance, clinical applications by anatomic site, and emerging topics including skin mark-less setups. Several dedicated chapters on SGRT for intracranial radiosurgery and breast, covering technical aspects, risk assessment and outcomes. Jeremy Hoisak, PhD, DABR is an Assistant Professor in the Department of Radiation Medicine and Applied Sciences at the University of California, San Diego. Dr. Hoisak’s clinical expertise includes radiosurgery and respiratory motion management. Adam Paxton, PhD, DABR is an Assistant Professor in the Department of Radiation Oncology at the University of Utah. Dr. Paxton’s clinical expertise includes patient safety, motion management, radiosurgery, and proton therapy. Benjamin Waghorn, PhD, DABR is the Director of Clinical Physics at Vision RT. Dr. Waghorn’s research interests include intensity modulated radiation therapy, motion management, and surface image guidance systems. Todd Pawlicki, PhD, DABR, FAAPM, FASTRO, is Professor and Vice-Chair for Medical Physics in the Department of Radiation Medicine and Applied Sciences at the University of California, San Diego. Dr. Pawlicki has published extensively on quality and safety in radiation therapy. He has served on the Board of Directors for the American Society for Radiology Oncology (ASTRO) and the American Association of Physicists in Medicine (AAPM).
Download or read book Prediction and Classification of Respiratory Motion written by Suk Jin Lee and published by Springer. This book was released on 2013-10-25 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin. In the first chapter following the Introduction to this book, we review three prediction approaches of respiratory motion: model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the following chapter, we present a phantom study—prediction of human motion with distributed body sensors—using a Polhemus Liberty AC magnetic tracker. Next we describe respiratory motion estimation with hybrid implementation of extended Kalman filter. The given method assigns the recurrent neural network the role of the predictor and the extended Kalman filter the role of the corrector. After that, we present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction, we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. We have evaluated the new algorithm by comparing the prediction overshoot and the tracking estimation value. The experimental results of 448 patients’ breathing patterns validated the proposed irregular breathing classifier in the last chapter.
Download or read book Adaptive Radiation Therapy written by X. Allen Li and published by CRC Press. This book was released on 2011-01-27 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern medical imaging and radiation therapy technologies are so complex and computer driven that it is difficult for physicians and technologists to know exactly what is happening at the point-of-care. Medical physicists responsible for filling this gap in knowledge must stay abreast of the latest advances at the intersection of medical imaging an
Download or read book Selected Papers written by Herbert Robbins and published by . This book was released on 1985 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Carbon Ion Radiotherapy written by Hirohiko Tsujii and published by Springer Science & Business Media. This book was released on 2013-12-25 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a practical guide for the use of carbon ions in cancer radiotherapy. On the basis of clinical experience with more than 7,000 patients with various types of tumors treated over a period of nearly 20 years at the National Institute of Radiological Sciences, step-by-step procedures and technological development of this modality are highlighted. The book is divided into two sections, the first covering the underlying principles of physics and biology, and the second section is a systematic review by tumor site, concentrating on the role of therapeutic techniques and the pitfalls in treatment planning. Readers will learn of the superior outcomes obtained with carbon-ion therapy for various types of tumors in terms of local control and toxicities. It is essential to understand that the carbon-ion beam is like a two-edged sword: unless it is used properly, it can increase the risk of severe injury to critical organs. In early series of dose-escalation studies, some patients experienced serious adverse effects such as skin ulcers, pneumonitis, intestinal ulcers, and bone necrosis, for which salvage surgery or hospitalization was required. To preclude such detrimental results, the adequacy of therapeutic techniques and dose fractionations was carefully examined in each case. In this way, significant improvements in treatment results have been achieved and major toxicities are no longer observed. With that knowledge, experts in relevant fields expand upon techniques for treatment delivery at each anatomical site, covering indications and optimal treatment planning. With its practical focus, this book will benefit radiation oncologists, medical physicists, medical dosimetrists, radiation therapists, and senior nurses whose work involves radiation therapy, as well as medical oncologists and others who are interested in radiation therapy.
Download or read book MRI of the Lung written by Hans-Ulrich Kauczor and published by Springer Science & Business Media. This book was released on 2008-11-12 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade significant developments have been achieved in the field of magnetic resonance imaging (MRI), enabling MRI to enter the clinical arena of chest imaging. Standard protocols can now be implemented on up-to-date scanners, allowing MRI to be used as a first-line imaging modality for various lung diseases, including cystic fibrosis, pulmonary hypertension and even lung cancer. The diagnostic benefits stem from the ability of MRI to visualize changes in lung structure while simultaneously imaging different aspects of lung function, such as perfusion, respiratory motion, ventilation and gas exchange. On this basis, novel quantitative surrogates for lung function can be obtained. This book provides a comprehensive overview of how to use MRI for imaging of lung disease. Special emphasis is placed on benign diseases requiring regular monitoring, given that it is patients with these diseases who derive the greatest benefit from the avoidance of ionizing radiation.
Download or read book New Technologies in Radiation Oncology written by Wolfgang C. Schlegel and published by Springer Science & Business Media. This book was released on 2006-01-27 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: - Summarizes the state of the art in the most relevant areas of medical physics and engineering applied to radiation oncology - Covers all relevant areas of the subject in detail, including 3D imaging and image processing, 3D treatment planning, modern treatment techniques, patient positioning, and aspects of verification and quality assurance - Conveys information in a readily understandable way that will appeal to professionals and students with a medical background as well as to newcomers to radiation oncology from the field of physics
