radiomics and its clinical application

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Radiomics and its Clinical Application
Author : Jie Tian,Di Dong,Zhenyu Liu,Jingwei Wei
Publisher : Academic Press
Release Date : 2021-05-01
ISBN 10 : 0128181028
Pages : 225 pages
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Radiomics and its Clinical Application: Artificial Intelligence and Medical Big Data describes the two key aspects of radiomic clinical practice, including precision diagnosis and the therapeutic effect and prognostic evaluation that 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, radiologists, pathologists, oncologists and surgeons wanting to understand radiomics and its potential in clinical practice. Provides an introduction to the concepts of radiomics Presents an in-depth discussion on core technologies and methods Summarizes current radiomics research, perspectives on the future of radiomics, and the challenges ahead Includes an introduction to several platforms that are planned to be built, including cooperation, data sharing, software and application platforms

Radiomics and Radiogenomics
Author : Ruijiang Li,Lei Xing,Sandy Napel,Daniel L. Rubin
Publisher : CRC Press
Release Date : 2019-07-09
ISBN 10 : 1351208268
Pages : 420 pages
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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 Medicine
Author : Lei Xing,Maryellen L. Giger,James K Min
Publisher : Academic Press
Release Date : 2020-09-16
ISBN 10 : 0128212586
Pages : 568 pages
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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

Handbook of Medical Image Computing and Computer Assisted Intervention
Author : S. Kevin Zhou,Daniel Rueckert,Gabor Fichtinger
Publisher : Academic Press
Release Date : 2019-10-18
ISBN 10 : 0128165863
Pages : 1072 pages
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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

Molecular Imaging in Oncology
Author : Otmar Schober,Burkhard Riemann
Publisher : Springer Science & Business Media
Release Date : 2012-11-28
ISBN 10 : 3642108539
Pages : 416 pages
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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 Medical Imaging
Author : Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publisher : Springer
Release Date : 2019-01-29
ISBN 10 : 3319948784
Pages : 373 pages
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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.

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging
Author : Kenji Suzuki,Yisong Chen
Publisher : Springer
Release Date : 2018-01-09
ISBN 10 : 331968843X
Pages : 387 pages
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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.

Glioma Imaging
Author : Whitney B. Pope
Publisher : Springer Nature
Release Date : 2019-11-11
ISBN 10 : 3030273598
Pages : 286 pages
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This book covers physiologic, metabolic and molecular imaging for gliomas. Gliomas are the most common primary brain tumors. Imaging is critical for glioma management because of its ability to noninvasively define the anatomic location and extent of disease. While conventional MRI is used to guide current treatments, multiple studies suggest molecular features of gliomas may be identified with noninvasive imaging, including physiologic MRI and amino acid positron emission tomography (PET). These advanced imaging techniques have the promise to help elucidate underlying tumor biology and provide important information that could be integrated into routine clinical practice. The text outlines current clinical practice including common scenarios in which imaging interpretation impacts patient management. Gaps in knowledge and potential areas of advancement based on the application of more experimental imaging techniques will be discussed. In reviewing this book, readers will learn: current standard imaging methodologies used in clinical practice for patients undergoing treatment for glioma and the implications of emerging treatment modalities including immunotherapy the theoretical basis for advanced imaging techniques including diffusion and perfusion MRI, MR spectroscopy, CEST and amino acid PET the relationship between imaging and molecular/genomic glioma features incorporated in the WHO 2016 classification update and the potential application of machine learning about the recently adopted and FDA approved standard brain tumor protocol for multicenter drug trials of the gaps in knowledge that impede optimal patient management and the cutting edge imaging techniques that could address these deficits

Handbook of Medical Image Computing and Computer Assisted Intervention
Author : S. Kevin Zhou,Daniel Rueckert,Gabor Fichtinger
Publisher : Academic Press
Release Date : 2019-10-18
ISBN 10 : 0128165863
Pages : 1072 pages
GET BOOK!

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

Clinical Nuclear Medicine
Author : Hojjat Ahmadzadehfar
Publisher : Springer Nature
Release Date :
ISBN 10 : 3030394573
Pages : 329 pages
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Machine Learning With Radiation Oncology Big Data
Author : Jun Deng,Issam El Naqa,Lei Xing
Publisher : Frontiers Media SA
Release Date : 2019-01-21
ISBN 10 : 2889457303
Pages : 329 pages
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Radiomics and Radiogenomics in Neuro-oncology
Author : Hassan Mohy-ud-Din,Saima Rathore
Publisher : Springer Nature
Release Date : 2020-02-24
ISBN 10 : 3030401243
Pages : 91 pages
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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.