Radiomics and Its Clinical Application

Radiomics and Its Clinical Application
Author: Jie Tian,Di Dong,Zhenyu Liu,Jingwei Wei
Publsiher: Academic Press
Total Pages: 300
Release: 2021-06-03
ISBN 10: 0128181028
ISBN 13: 9780128181027
Language: EN, FR, DE, ES & NL

Radiomics and Its Clinical Application Book Review:

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
Author: Ruijiang Li,Lei Xing,Sandy Napel,Daniel L. Rubin
Publsiher: CRC Press
Total Pages: 420
Release: 2019-07-09
ISBN 10: 1351208268
ISBN 13: 9781351208260
Language: EN, FR, DE, ES & NL

Radiomics and Radiogenomics Book Review:

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

Big Data in Radiation Oncology

Big Data in Radiation Oncology
Author: Jun Deng,Lei Xing
Publsiher: CRC Press
Total Pages: 289
Release: 2019-03-07
ISBN 10: 1351801120
ISBN 13: 9781351801126
Language: EN, FR, DE, ES & NL

Big Data in Radiation Oncology Book Review:

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.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Lei Xing,Maryellen L. Giger,James K. Min
Publsiher: Academic Press
Total Pages: 568
Release: 2020-09-03
ISBN 10: 0128212586
ISBN 13: 9780128212585
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

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
Author: Otmar Schober,Burkhard Riemann
Publsiher: Springer Science & Business Media
Total Pages: 416
Release: 2012-11-28
ISBN 10: 3642108539
ISBN 13: 9783642108532
Language: EN, FR, DE, ES & NL

Molecular Imaging in Oncology Book Review:

The impact of molecular imaging on diagnostics, therapy, and follow-up in oncology is increasing steadily. Many innovative molecular imaging probes have already entered clinical practice, and there is no doubt that the future emphasis will be on multimodality imaging in which morphological, functional, and molecular imaging techniques are combined in a single clinical investigation. This handbook addresses all aspects of molecular imaging in oncology, from basic research to clinical applications. The first section is devoted to technology and probe design, and examines a variety of PET and SPECT tracers as well as multimodality probes. Preclinical studies are then discussed in detail, with particular attention to multimodality imaging. In the third section, diverse clinical applications are presented, and the book closes by looking at future challenges. This handbook will be of value to all who are interested in the revolution in diagnostic oncology that is being brought about by molecular imaging.

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging
Author: Kenji Suzuki,Yisong Chen
Publsiher: Springer
Total Pages: 387
Release: 2018-01-09
ISBN 10: 331968843X
ISBN 13: 9783319688435
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging Book Review:

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.

Meta Learning With Medical Imaging and Health Informatics Applications

Meta Learning With Medical Imaging and Health Informatics Applications
Author: Hien Van Nguyen,Ronald Summers,Rama Chellappa
Publsiher: Academic Press
Total Pages: 430
Release: 2022-09-30
ISBN 10: 0323998526
ISBN 13: 9780323998529
Language: EN, FR, DE, ES & NL

Meta Learning With Medical Imaging and Health Informatics Applications Book Review:

Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks’ fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks. This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions. The book comes with a GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly. First book on applying Meta Learning to medical imaging Pioneers in the field as contributing authors to explain the theory and its development Has GitHub repository consisting of various code examples and documentation to help the audience to set up Meta-Learning algorithms for their applications quickly

Meningioma From Basic Research to Clinical Translational Study

Meningioma  From Basic Research to Clinical Translational Study
Author: Hailiang Tang,Allen Ho
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2021-12-29
ISBN 10: 2889718700
ISBN 13: 9782889718702
Language: EN, FR, DE, ES & NL

Meningioma From Basic Research to Clinical Translational Study Book Review:

Clinical Applications of SPECT CT

Clinical Applications of SPECT CT
Author: Hojjat Ahmadzadehfar,Hans-Jürgen Biersack,Ken Herrmann
Publsiher: Springer Nature
Total Pages: 320
Release: 2021-12-09
ISBN 10: 3030658503
ISBN 13: 9783030658502
Language: EN, FR, DE, ES & NL

Clinical Applications of SPECT CT Book Review:

This book, now in a revised and updated second edition, covers the full spectrum of clinical applications of SPECT/CT in the diagnosis and therapy planning of benign and malignant diseases. All chapters have been thoroughly updated and some chapters have been completely rewritten by a new group of experts. The opening chapters discuss the technology and physics of SPECT/CT and its use in dosimetry. The role of SPECT/CT in the imaging of a range of pathologic conditions is then addressed in detail. Applications covered include imaging of the thyroid, neuroendocrine tumors, bone, cardiac scintigraphy, sentinel node scintigraphy and imaging of the lungs. Individual chapters are also devoted to therapy planning in selective internal radiation therapy of liver tumors and to Bremsstrahlung SPECT/CT. For Nuclear Medicine Physicians, Radiologists and medical students in this field, the book offers an essential and up-to-date source of information on this invaluable hybrid imaging technique.

Big Data Analytics for Healthcare

Big Data Analytics for Healthcare
Author: Pantea Keikhosrokiani
Publsiher: Academic Press
Total Pages: 354
Release: 2022-05-19
ISBN 10: 0323985165
ISBN 13: 9780323985161
Language: EN, FR, DE, ES & NL

Big Data Analytics for Healthcare Book Review:

Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work. Presents theories, methods and approaches in which data analytic techniques are used for medical data Brings practical information on how to use big data for classification, diagnosis, treatment, and prediction of diseases Discusses social, behavioral, and medical fake news analytics for medical information systems

AI in Biological and Biomedical Imaging

AI in Biological and Biomedical Imaging
Author: Xin Gao,Lihua Li,Min Xu
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2022-01-17
ISBN 10: 2889740498
ISBN 13: 9782889740499
Language: EN, FR, DE, ES & NL

AI in Biological and Biomedical Imaging Book Review:

Doctors Gao and Li hold patents related to artificial intelligence.

Neuroimaging Techniques in Clinical Practice

Neuroimaging Techniques in Clinical Practice
Author: Manoj Mannil,Sebastian F.-X. Winklhofer
Publsiher: Springer Nature
Total Pages: 342
Release: 2020-08-11
ISBN 10: 303048419X
ISBN 13: 9783030484194
Language: EN, FR, DE, ES & NL

Neuroimaging Techniques in Clinical Practice Book Review:

This book provides a concise overview of emerging technologies in the field of modern neuroimaging. Fundamental principles of the main imaging modalities are described as well as advanced imaging techniqes including diffusion weighted imaging, perfusion imaging, arterial spin labeling, diffusion tensor imaging, intravoxel incoherent motion, MR spectroscopy, functional MRI, and artificial intelligence. The physical concepts underlying each imaging technique are carefully and clearly explained in a way suited to a medical audience without prior technical knowledge. In addition, the clinical applications of the various techniques are described with the aid of illustrative clinical examples. Helpful background information is also presented on the core principles of MRI and the evolution of neuroimaging, and important references to current medical research are highlighted. The book will meet the needs of a range of non-technological professionals with an interest in advanced neuroimaging, including radiology researchers and clinicians in the fields of neurology, neurosurgery, and psychiatry.

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
Author: Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
Publsiher: Academic Press
Total Pages: 454
Release: 2020-11-20
ISBN 10: 0128202742
ISBN 13: 9780128202746
Language: EN, FR, DE, ES & NL

Machine Learning in Cardiovascular Medicine Book Review:

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Novel Methods for Oncologic Imaging Analysis Radiomics Machine Learning and Artificial Intelligence

Novel Methods for Oncologic Imaging Analysis  Radiomics  Machine Learning  and Artificial Intelligence
Author: Xuelei Ma,Lei Deng,Rong Tian,Chunxiao Guo
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2021-09-23
ISBN 10: 2889713474
ISBN 13: 9782889713479
Language: EN, FR, DE, ES & NL

Novel Methods for Oncologic Imaging Analysis Radiomics Machine Learning and Artificial Intelligence Book Review:

Ultrasound in Oncology Application of Big Data and Artificial Intelligence

Ultrasound in Oncology  Application of Big Data and Artificial Intelligence
Author: Hui-Xiong Xu,Wei Wang,Richard Gary Barr,Katsutoshi Sugimoto
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2022-02-09
ISBN 10: 288974311X
ISBN 13: 9782889743117
Language: EN, FR, DE, ES & NL

Ultrasound in Oncology Application of Big Data and Artificial Intelligence Book Review:

Radiomics and Radiogenomics

Radiomics and Radiogenomics
Author: Ruijiang Li,Lei Xing,Sandy Napel,Daniel L. Rubin
Publsiher: CRC Press
Total Pages: 501
Release: 2019-07-09
ISBN 10: 135120825X
ISBN 13: 9781351208253
Language: EN, FR, DE, ES & NL

Radiomics and Radiogenomics Book Review:

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

Biomarkers in Genitourinary Cancers Volume I

Biomarkers in Genitourinary Cancers  Volume I
Author: Eric A. Singer,Paula Alexandra Quintela Videira,Marco Borghesi
Publsiher: Frontiers Media SA
Total Pages: 226
Release: 2022-05-25
ISBN 10: 2889762157
ISBN 13: 9782889762156
Language: EN, FR, DE, ES & NL

Biomarkers in Genitourinary Cancers Volume I Book Review:

Imaging in Clinical Oncology

Imaging in Clinical Oncology
Author: Athanasios D. Gouliamos,John A. Andreou,Paris A. Kosmidis
Publsiher: Springer
Total Pages: 709
Release: 2018-10-04
ISBN 10: 3319688731
ISBN 13: 9783319688732
Language: EN, FR, DE, ES & NL

Imaging in Clinical Oncology Book Review:

This is the second edition of a well-received book reflecting the state of the art in oncologic imaging research and promoting mutual understanding and collaboration between radiologists and clinical oncologists. It presents all currently available imaging modalities and covers a broad spectrum of oncologic diseases for most organ systems. Today, oncologic imaging faces the challenge of improving and refining concepts for precise tumor delineation and biologic/functional tumor characterization, as well as for purposes of creating individual treatment plans. The concept of radiomics has further advanced the conversion of images into mineable data and subsequent analysis of said data for decision-making support. Since the release of the book’s first edition, radiomics has been introduced in oncology studies and can be performed with tomographic images from CT, MRI and PET/CT studies. The combination of radiomic data with genomic features is known as radiogenomics, and can potentially offer additional decision-making support. This book will be of interest to clinical oncologists with regard to the diagnosis, staging, treatment and follow-up on various tumors affecting the CNS, chest, abdomen, urogenital and musculoskeletal systems.

The Application of Radiomics and Artificial Intelligence in Cancer Imaging

The Application of Radiomics and Artificial Intelligence in Cancer Imaging
Author: Jiuquan Zhang,Hong Huang,Wenli Cai
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2022-03-21
ISBN 10: 2889747441
ISBN 13: 9782889747443
Language: EN, FR, DE, ES & NL

The Application of Radiomics and Artificial Intelligence in Cancer Imaging Book Review:

Breakthrough in Imaging Guided Precision Medicine in Oncology

Breakthrough in Imaging Guided Precision Medicine in Oncology
Author: Laurent Dercle,Samy Ammari,Florent L. Besson,Fatima-Zohra Mokrane,Romain-David Seban,Randy Yeh
Publsiher: Frontiers Media SA
Total Pages: 337
Release: 2022-03-11
ISBN 10: 2889746542
ISBN 13: 9782889746545
Language: EN, FR, DE, ES & NL

Breakthrough in Imaging Guided Precision Medicine in Oncology Book Review: