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 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 Medical Imaging and Augmented Reality written by Guoyan Zheng and published by Springer. This book was released on 2016-08-13 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 6th International Conference on Medical Imaging and Augmented Reality, MIAR 2016, was held in Bern, Switzerland during August 2016. The aim of MIAR is to bring together researchers in computer vision, graphics, robotics, and medical imaging to present the state-of-the-art developments in this ever-growing research area in topics such as: Medical Image Formation, Analysis and Interpretation Augmented Reality, Visualization and Simulation Computer Assisted Interventional and Robotics, Surgical Planning Systematic Extra- and Intra-corporeal Imaging Modalities General Biological and Neuroscience Image Computing
Download or read book Data Driven Treatment Response Assessment and Preterm Perinatal and Paediatric Image Analysis written by Andrew Melbourne and published by Springer. This book was released on 2018-09-14 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the First International Workshop on Data Driven Treatment Response Assessment, DATRA 2018 and the Third International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 5 full papers presented at DATRA 2018 and the 12 full papers presented at PIPPI 2018 were carefully reviewed and selected. The DATRA papers cover a wide range of exploring pattern recognition technologies for tackling clinical issues related to the follow-up analysis of medical data with focus on malignancy progression analysis, computer-aided models of treatment response, and anomaly detection in recovery feedback. The PIPPI papers cover topics of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period.
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 Compensating for Quasi periodic Motion in Robotic Radiosurgery written by Floris Ernst and published by Springer Science & Business Media. This book was released on 2011-11-18 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compensating for Quasi-periodic Motion in Robotic Radiosurgery outlines the techniques needed to accurately track and compensate for respiratory and pulsatory motion during robotic radiosurgery. The algorithms presented within the book aid in the treatment of tumors that move during respiration. In Chapters 1 and 2, the book introduces the concept of stereotactic body radiation therapy, motion compensation strategies and the clinical state-of-the-art. In Chapters 3 through 5, the author describes and evaluates new methods for motion prediction, for correlating external motion to internal organ motion, and for the evaluation of these algorithms’ output based on an unprecedented amount of real clinical data. Finally, Chapter 6 provides a brief introduction into currently investigated, open questions and further fields of research. Compensating for Quasi-periodic Motion in Robotic Radiosurgery targets researchers working in the related fields of surgical oncology, artificial intelligence, robotics and more. Advanced-level students will also find this book valuable.
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 Artificial Intelligence for Precision Medicine written by Jun Deng and published by Frontiers Media SA. This book was released on 2022-02-16 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Imaging in non small cell lung cancer written by Yiyan Liu and published by Frontiers Media SA. This book was released on 2023-04-19 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine and Deep Learning in Oncology Medical Physics and Radiology written by Issam El Naqa and published by Springer Nature. This book was released on 2022-02-02 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Download or read book Machine Learning With Radiation Oncology Big Data written by Jun Deng and published by Frontiers Media SA. This book was released on 2019-01-21 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep learning approaches in image guided diagnosis for tumors written by Shahid Mumtaz and published by Frontiers Media SA. This book was released on 2023-03-13 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optical Methods in Sensing and Imaging for Medical and Biological Applications written by Dragan Indjin and published by MDPI. This book was released on 2019-01-24 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Optical Methods in Sensing and Imaging for Medical and Biological Applications" that was published in Sensors
Download or read book Statistical Atlases and Computational Models of the Heart Regular and CMRxMotion Challenge Papers written by Oscar Camara and published by Springer Nature. This book was released on 2023-01-27 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 13th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2022, held in conjunction with the 25th MICCAI conference. The 34 regular workshop papers included in this volume were carefully reviewed and selected after being revised and deal with topics such as: common cardiac segmentation and modelling problems to more advanced generative modelling for ageing hearts, learning cardiac motion using biomechanical networks, physics-informed neural networks for left atrial appendage occlusion, biventricular mechanics for Tetralogy of Fallot, ventricular arrhythmia prediction by using graph convolutional network, and deeper analysis of racial and sex biases from machine learning-based cardiac segmentation. In addition, 14 papers from the CMRxMotion challenge are included in the proceedings which aim to assess the effects of respiratory motion on cardiac MRI (CMR) imaging quality and examine the robustness of segmentation models in face of respiratory motion artefacts. A total of 48 submissions to the workshop was received.
Download or read book Database and Expert Systems Applications written by Sven Hartmann and published by Springer. This book was released on 2018-08-20 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set of LNCS 11029 and LNCS 11030 constitutes the refereed proceedings of the 29th International Conference on Database and Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018. The 35 revised full papers presented together with 40 short papers were carefully reviewed and selected from 160 submissions. The papers of the first volume discuss a range of topics including: Big data analytics; data integrity and privacy; decision support systems; data semantics; cloud data processing; time series data; social networks; temporal and spatial databases; and graph data and road networks. The papers of the second volume discuss a range of the following topics: Information retrieval; uncertain information; data warehouses and recommender systems; data streams; information networks and algorithms; database system architecture and performance; novel database solutions; graph querying and databases; learning; emerging applications; data mining; privacy; and text processing.
Download or read book Digital Signal Processing with Kernel Methods written by Jose Luis Rojo-Alvarez and published by John Wiley & Sons. This book was released on 2018-02-05 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors: http://github.com/DSPKM • Presents the necessary basic ideas from both digital signal processing and machine learning concepts • Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing • Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.
Download or read book Breakthrough in Imaging Guided Precision Medicine in Oncology written by Laurent Dercle and published by Frontiers Media SA. This book was released on 2022-03-11 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt:
