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Radiomics and Its Clinical Application

Radiomics and Its Clinical Application
Artificial Intelligence and Medical Big Data

by Jie Tian,Di Dong,Zhenyu Liu,Jingwei Wei

  • Publisher : Academic Press
  • Release : 2021-06-18
  • Pages : 300
  • ISBN : 0128181028
  • Language : En, Es, Fr & De
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The rapid development of artificial intelligence technology in medical data analysis has led to the concept of radiomics. This book introduces the essential and latest technologies in radiomics, such as imaging segmentation, quantitative imaging feature extraction, and machine learning methods for model construction and performance evaluation, providing invaluable guidance for the researcher entering the field. It fully describes three key aspects of radiomic clinical practice: precision diagnosis, the therapeutic effect, and prognostic evaluation, which make radiomics a powerful tool in the clinical setting. This book is a very useful resource for scientists and computer engineers in machine learning and medical image analysis, scientists focusing on antineoplastic drugs, and radiologists, pathologists, oncologists, as well as surgeons wanting to understand radiomics and its potential in clinical practice. An introduction to the concepts of radiomics In-depth presentation of the core technologies and methods Summary of current radiomics research, perspective on the future of radiomics and the challenges ahead An introduction to several platforms that are planned to be built: cooperation, data sharing, software, and application platforms

Radiomics and Radiogenomics

Radiomics and Radiogenomics
Technical Basis and Clinical Applications

by Ruijiang Li,Lei Xing,Sandy Napel,Daniel L. Rubin

  • Publisher : CRC Press
  • Release : 2019-07-09
  • Pages : 420
  • ISBN : 1351208268
  • Language : En, Es, Fr & De
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Radiomics and Radiogenomics: Technical Basis and Clinical Applications provides a first summary of the overlapping fields of radiomics and radiogenomics, showcasing how they are being used to evaluate disease characteristics and correlate with treatment response and patient prognosis. It explains the fundamental principles, technical bases, and clinical applications with a focus on oncology. The book’s expert authors present computational approaches for extracting imaging features that help to detect and characterize disease tissues for improving diagnosis, prognosis, and evaluation of therapy response. This book is intended for audiences including imaging scientists, medical physicists, as well as medical professionals and specialists such as diagnostic radiologists, radiation oncologists, and medical oncologists. Features Provides a first complete overview of the technical underpinnings and clinical applications of radiomics and radiogenomics Shows how they are improving diagnostic and prognostic decisions with greater efficacy Discusses the image informatics, quantitative imaging, feature extraction, predictive modeling, software tools, and other key areas Covers applications in oncology and beyond, covering all major disease sites in separate chapters Includes an introduction to basic principles and discussion of emerging research directions with a roadmap to clinical translation

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging
A Book

by Kenji Suzuki,Yisong Chen

  • Publisher : Springer
  • Release : 2018-01-09
  • Pages : 387
  • ISBN : 331968843X
  • Language : En, Es, Fr & De
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This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an “information overload” for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field.

Radiomics and Radiogenomics

Radiomics and Radiogenomics
A Book

by Taylor & Francis Group

  • Publisher : Unknown Publisher
  • Release : 2021-03-31
  • Pages : 329
  • ISBN : 9780367779580
  • Language : En, Es, Fr & De
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Handbook of Medical Image Computing and Computer Assisted Intervention

Handbook of Medical Image Computing and Computer Assisted Intervention
A Book

by S. Kevin Zhou,Daniel Rueckert,Gabor Fichtinger

  • Publisher : Academic Press
  • Release : 2019-10-18
  • Pages : 1072
  • ISBN : 0128165863
  • Language : En, Es, Fr & De
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Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention. Presents the key research challenges in medical image computing and computer-assisted intervention Written by leading authorities of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society Contains state-of-the-art technical approaches to key challenges Demonstrates proven algorithms for a whole range of essential medical imaging applications Includes source codes for use in a plug-and-play manner Embraces future directions in the fields of medical image computing and computer-assisted intervention

Machine Learning With Radiation Oncology Big Data

Machine Learning With Radiation Oncology Big Data
A Book

by Jun Deng,Issam El Naqa,Lei Xing

  • Publisher : Frontiers Media SA
  • Release : 2019-01-21
  • Pages : 329
  • ISBN : 2889457303
  • Language : En, Es, Fr & De
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Proceedings of the 2nd International Conference on Healthcare Science and Engineering

Proceedings of the 2nd International Conference on Healthcare Science and Engineering
A Book

by Chase Q. Wu,Ming-Chien Chyu,Jaime Lloret,Xianxian Li

  • Publisher : Springer
  • Release : 2019-05-09
  • Pages : 306
  • ISBN : 9811368376
  • Language : En, Es, Fr & De
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This book presents a compilation of selected papers from the 2nd International Conference on Healthcare Science and Engineering (Healthcare 2018). The work focuses on novel computing, networking, and data analytics techniques for various issues in healthcare. The book is a valuable resource for academic researchers and practitioners working in the field.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Technical Basis and Clinical Applications

by Lei Xing,Maryellen L. Giger,James K Min

  • Publisher : Academic Press
  • Release : 2020-09-16
  • Pages : 568
  • ISBN : 0128212586
  • Language : En, Es, Fr & De
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Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Molecular Imaging in Oncology

Molecular Imaging in Oncology
A Book

by Otmar Schober,Fabian Kiessling,Jürgen Debus

  • Publisher : Springer Nature
  • Release : 2020-06-27
  • Pages : 918
  • ISBN : 3030426181
  • Language : En, Es, Fr & De
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This book discusses the most significant recent advances in oncological molecular imaging, covering the full spectrum from basic and preclinical research to clinical practice. The content is divided into five sections, the first of which is devoted to standardized and emerging technologies and probe designs for different modalities, such as PET, SPECT, optical and optoacoustic imaging, ultrasound, CT, and MRI. The second section focuses on multiscale preclinical applications ranging from advanced microscopy and mass spectroscopy to whole-body imaging. In the third section, various clinical applications are presented, including image-guided surgery and the radiomic analysis of multiple imaging features. The final two sections are dedicated to the emerging, crucial role that molecular imaging can play in the planning and monitoring of external and internal radiotherapy, and to future challenges and prospects in multimodality imaging. Given its scope, the handbook will benefit all readers who are interested in the revolution in diagnostic and therapeutic oncology that is now being brought about by molecular imaging.

Radiomics and Radiogenomics in Neuro-oncology

Radiomics and Radiogenomics in Neuro-oncology
First International Workshop, RNO-AI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

by Hassan Mohy-ud-Din,Saima Rathore

  • Publisher : Springer Nature
  • Release : 2020-02-24
  • Pages : 91
  • ISBN : 3030401243
  • Language : En, Es, Fr & De
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This book constitutes the proceedings of the First International Workshop on Radiomics and Radiogenomics in Neuro-oncology, RNO-AI 2019, which was held in conjunction with MICCAI in Shenzhen, China, in October 2019. The 10 full papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the development of tools that can automate the analysis and synthesis of neuro-oncologic imaging.

Clinical Nuclear Medicine

Clinical Nuclear Medicine
A Book

by Hojjat Ahmadzadehfar,Hans-Jürgen Biersack,Leonard M. Freeman,Lionel S. Zuckier

  • Publisher : Springer Nature
  • Release : 2020-05-06
  • Pages : 1029
  • ISBN : 3030394573
  • Language : En, Es, Fr & De
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In the new edition of this very successful book, European and North American experts present the state of the art in diagnostic and therapeutic radionuclide procedures. The aim is to examine established and emerging clinical applications in detail, rather than to consider everything included in the comprehensive texts already available within the field. This “practical” approach ensures that the book will be a valuable guide for nuclear medicine physicians, technologists, students, and interested clinicians alike. This edition of Clinical Nuclear Medicine has been extensively revised to take account of recent developments. The roles of SPECT/CT, PET/CT, and PET/MRI are clearly explained and illustrated, and the coverage extended to encompass, for example, novel PET tracers and therapeutic radionuclides, advanced techniques of brain imaging, and the development of theranostics. Readers will be fully persuaded of the ever-increasing value of nuclear medicine techniques in depicting physiology and function and complementing anatomic modalities such as CT, MRI, and ultrasound.

Precision Medicine in Cancer Therapy

Precision Medicine in Cancer Therapy
A Book

by Daniel D. Von Hoff,Haiyong Han

  • Publisher : Springer
  • Release : 2019-06-17
  • Pages : 283
  • ISBN : 3030163911
  • Language : En, Es, Fr & De
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This book presents the latest advances in precision medicine in some of the most common cancer types, including hematological, lung and breast malignancies. It also discusses emerging technologies that are making a significant impact on precision medicine in cancer therapy. In addition to describing specific approaches that have already entered clinical practice, the book explores new concepts and tools that are being developed. Precision medicine aims to deliver personalized healthcare tailored to a patient’s genetics, lifestyle and environment, and cancer therapy is one of the areas in which it has flourished in recent years. Documenting the latest advances, this book is of interest to physicians and clinical fellows in the front line of the war on cancer, as well as to basic scientists working in the fields of cancer biology, drug development, biomarker discovery, and biomedical engineering. The contributing authors include translational physicians with first-hand experience in precision patient care.

Magnetic Resonance Imaging for Radiation Therapy

Magnetic Resonance Imaging for Radiation Therapy
A Book

by Ning Wen,Yue Cao,Jing Cai

  • Publisher : Frontiers Media SA
  • Release : 2020-06-04
  • Pages : 329
  • ISBN : 288963762X
  • Language : En, Es, Fr & De
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Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
From Theory to Clinical Practice

by Lia Morra,Silvia Delsanto,Loredana Correale

  • Publisher : CRC Press
  • Release : 2019-11-25
  • Pages : 152
  • ISBN : 1000753085
  • Language : En, Es, Fr & De
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This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Understanding COVID-19: The Role of Computational Intelligence

Understanding COVID-19: The Role of Computational Intelligence
A Book

by Janmenjoy Nayak

  • Publisher : Springer Nature
  • Release : 2021
  • Pages : 329
  • ISBN : 3030747611
  • Language : En, Es, Fr & De
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Modeling for Prediction of Radiation-Induced Toxicity to Improve Therapeutic Ratio in the Modern Radiation Therapy Era

Modeling for Prediction of Radiation-Induced Toxicity to Improve Therapeutic Ratio in the Modern Radiation Therapy Era
A Book

by Ester Orlandi,Tiziana Rancati,Giuseppe Sanguineti,Claudio Fiorino,Riccardo Valdagni

  • Publisher : Frontiers Media SA
  • Release : 2021-07-27
  • Pages : 329
  • ISBN : 2889710882
  • Language : En, Es, Fr & De
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Big Data in Radiation Oncology

Big Data in Radiation Oncology
A Book

by Jun Deng,Lei Xing

  • Publisher : CRC Press
  • Release : 2019-03-07
  • Pages : 289
  • ISBN : 1351801120
  • Language : En, Es, Fr & De
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Big Data in Radiation Oncology gives readers an in-depth look into how big data is having an impact on the clinical care of cancer patients. While basic principles and key analytical and processing techniques are introduced in the early chapters, the rest of the book turns to clinical applications, in particular for cancer registries, informatics, radiomics, radiogenomics, patient safety and quality of care, patient-reported outcomes, comparative effectiveness, treatment planning, and clinical decision-making. More features of the book are: Offers the first focused treatment of the role of big data in the clinic and its impact on radiation therapy. Covers applications in cancer registry, radiomics, patient safety, quality of care, treatment planning, decision making, and other key areas. Discusses the fundamental principles and techniques for processing and analysis of big data. Address the use of big data in cancer prevention, detection, prognosis, and management. Provides practical guidance on implementation for clinicians and other stakeholders. Dr. Jun Deng is a professor at the Department of Therapeutic Radiology of Yale University School of Medicine and an ABR board certified medical physicist at Yale-New Haven Hospital. He has received numerous honors and awards such as Fellow of Institute of Physics in 2004, AAPM Medical Physics Travel Grant in 2008, ASTRO IGRT Symposium Travel Grant in 2009, AAPM-IPEM Medical Physics Travel Grant in 2011, and Fellow of AAPM in 2013. Lei Xing, Ph.D., is the Jacob Haimson Professor of Medical Physics and Director of Medical Physics Division of Radiation Oncology Department at Stanford University. His research has been focused on inverse treatment planning, tomographic image reconstruction, CT, optical and PET imaging instrumentations, image guided interventions, nanomedicine, and applications of molecular imaging in radiation oncology. Dr. Xing is on the editorial boards of a number of journals in radiation physics and medical imaging, and is recipient of numerous awards, including the American Cancer Society Research Scholar Award, The Whitaker Foundation Grant Award, and a Max Planck Institute Fellowship.

Increasing 18f-Fdg Pet/ct Capabilities In Radiotherapy For Lung And Esophageal Cancer Via Image Feature Analysis

Increasing 18f-Fdg Pet/ct Capabilities In Radiotherapy For Lung And Esophageal Cancer Via Image Feature Analysis
A Book

by Jasmine Alexandria Oliver

  • Publisher : Unknown Publisher
  • Release : 2016
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Also, certain feature groups were more affected by noise than others. For instance, contour-dependent shape features exhibited the least change with noise. Comparatively, GLSZM features exhibited the greatest change with added noise. Discordance was discovered between the inferior and superior tumor fiducial markers and metabolic tumor volume (MTV). This demonstrated a need for both fiducial markers and MTV to provide a comprehensive view of a tumor. These studies called attention to the differences in features caused by factors such as motion, acquisition parameters, and noise, etc. Investigators should be aware of these effects. PET/CT radiomic features are indeed highly affected by noise and motion. For accurate clinical use, these effects must be account by investigators and future clinical users. Further investigation is warranted towards the standardization of PET/CT radiomic feature acquisition and clinical application.

Precision Medicine for Investigators, Practitioners and Providers

Precision Medicine for Investigators, Practitioners and Providers
A Book

by Joel Faintuch,Salomao Faintuch

  • Publisher : Academic Press
  • Release : 2019-11-16
  • Pages : 640
  • ISBN : 0128191791
  • Language : En, Es, Fr & De
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Precision Medicine for Investigators, Practitioners and Providers addresses the needs of investigators by covering the topic as an umbrella concept, from new drug trials to wearable diagnostic devices, and from pediatrics to psychiatry in a manner that is up-to-date and authoritative. Sections include broad coverage of concerning disease groups and ancillary information about techniques, resources and consequences. Moreover, each chapter follows a structured blueprint, so that multiple, essential items are not overlooked. Instead of simply concentrating on a limited number of extensive and pedantic coverages, scholarly diagrams are also included. Provides a three-pronged approach to precision medicine that is focused on investigators, practitioners and healthcare providers Covers disease groups and ancillary information about techniques, resources and consequences Follows a structured blueprint, ensuring essential chapters items are not overlooked

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Opportunities, Applications and Risks

by Erik R. Ranschaert,Sergey Morozov,Paul R. Algra

  • Publisher : Springer
  • Release : 2019-02-07
  • Pages : 373
  • ISBN : 9783319948775
  • Language : En, Es, Fr & De
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This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.