Radiomics and Its Clinical Application

Radiomics and Its Clinical Application
Author: Jie Tian,Di Dong,Zhenyu Liu,Jingwei Wei
Publsiher: Academic Press
Total Pages: 302
Release: 2021-06-03
Genre: Computers
ISBN: 9780128181027

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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
Author: Ruijiang Li,Lei Xing,Sandy Napel,Daniel L. Rubin
Publsiher: CRC Press
Total Pages: 420
Release: 2019-07-09
Genre: Science
ISBN: 9781351208260

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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

Big Data in Radiation Oncology

Big Data in Radiation Oncology
Author: Jun Deng,Lei Xing
Publsiher: CRC Press
Total Pages: 355
Release: 2019-03-07
Genre: Science
ISBN: 9781351801119

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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.

Resistance to Tyrosine Kinase Inhibitors

Resistance to Tyrosine Kinase Inhibitors
Author: Daniele Focosi
Publsiher: Springer
Total Pages: 188
Release: 2016-11-07
Genre: Medical
ISBN: 9783319460918

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The volume will serve as a primer on tyrosine kinase signaling and its importance in cancer. The volume will first introduce the common denominators of small-molecule and antibody-derived inhibitors, as well as the general phenomenon of resistance. The volume will then detail resistance to the most commonly used classes of tyrosine kinase inhibitors, and will focus specific chapters on resistance to BCR-ABL1, FLT3, angiokinase family members, and ALK inhibitors.

Clinical Applications of SPECT CT

Clinical Applications of SPECT CT
Author: Hojjat Ahmadzadehfar,Hans-Jürgen Biersack
Publsiher: Springer Science & Business Media
Total Pages: 304
Release: 2013-12-05
Genre: Medical
ISBN: 9783642352836

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​ SPECT/CT cameras have considerably improved diagnostic accuracy in recent years based in large part on the better localization and definition of scintigraphic findings. This book covers the full spectrum of clinical applications of SPECT/CT in diagnosis and therapy planning of benign and malignant diseases. Opening chapters discuss the technology and physics of SPECT/CT and its use for dosimetry. The role of SPECT/CT in the imaging of a range of pathologic conditions is then addressed in detail. Applications covered include, among others, imaging of the thyroid, bone, and lungs, imaging of neuroendocrine tumors, cardiac scintigraphy, and sentinel node scintigraphy. Individual chapters are also devoted to therapy planning in selective internal radiation therapy of liver tumors and bremsstrahlung SPECT/CT. Readers will find this book to be an essential and up-to-date source of information on this invaluable hybrid imaging technique.

Radiomics and Radiogenomics in Neuro oncology

Radiomics and Radiogenomics in Neuro oncology
Author: Hassan Mohy-ud-Din,Saima Rathore
Publsiher: Springer Nature
Total Pages: 100
Release: 2020-02-24
Genre: Computers
ISBN: 9783030401245

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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.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publsiher: Springer
Total Pages: 373
Release: 2019-01-29
Genre: Medical
ISBN: 9783319948782

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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.

Fundamentals of Oncologic PET CT E Book

Fundamentals of Oncologic PET CT E Book
Author: Gary A. Ulaner
Publsiher: Elsevier Health Sciences
Total Pages: 352
Release: 2018-06-21
Genre: Medical
ISBN: 9780323568678

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In the fast-changing age of precision medicine, PET/CT is increasingly important for accurate cancer staging and evaluation of treatment response. Fundamentals of Oncologic PET/CT, by Dr. Gary A. Ulaner, offers an organized, systematic introduction to reading and interpreting PET/CT studies, ideal for radiology and nuclear medicine residents, practicing radiologists, medical oncologists, and radiation oncologists. Synthesizing eight years’ worth of cases and lectures from one of the largest cancer centers in the world, this title provides a real-world, practical approach, taking you through the body organ by organ as it explains how to integrate both the FDG PET and CT findings to best interpret each lesion.