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Radiomics and its Clinical Application - 1st Edition - ISBN: 9780128181010

Radiomics and its Clinical Application

1st Edition

Artificial Intelligence and Medical Big Data

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Authors: Jie Tian Di Dong Zhenyu Liu Jingwei Wei
Paperback ISBN: 9780128181010
Imprint: Academic Press
Published Date: 1st March 2021
Page Count: 225
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Description

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.

Key Features

  • 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

Readership

Researchers and graduate students in biomedical engineering, medical imaging, computer vision

Table of Contents

  1. Introduction of Radiomics
    2. Key technology of Radiomics
    3. Precision diagnosis based on Radiomics
    4. Therapeutic effect evaluation and prognostic prediction based on Radiomics
    5. Summary and outlook

Details

No. of pages:
225
Language:
English
Copyright:
© Academic Press 2021
Published:
1st March 2021
Imprint:
Academic Press
Paperback ISBN:
9780128181010

About the Authors

Jie Tian

Dr. Jie Tian received his PhD degree (with honors) in artificial intelligence from the Chinese Academy of Sciences in 1993. Since 1997, he has been a professor at the Chinese Academy of Sciences. Dr. Tian has been elected as the Fellow of ISMRM, AIMBE, IAMBE, IEEE, OSA, SPIE, and IAPR. He serves as the editorial board member of Molecular Imaging and Biology, European Radiology, IEEE Transactions on Medical Imaging, IEEE Transactions on Biomedical Engineering, IEEE Journal of Biomedical and Health Informatics and Photoacoustics. He is the author of over 400 peer-reviewed journal articles, including publication in Nature Biomedical Engineering, Science Advances, Journal of Clinical Oncology, Nature Communications , Radiology, IEEE Transactions on Medical Imaging, and many other journals, and these articles received over 25,000 Google Scholar citations(H-index 79). Dr. Tian is recognized as a pioneer and a leader in China in the field of molecular imaging. In the last two decades, he has developed a series of new optical imaging models and reconstruction algorithms for in vivo optical tomographic imaging, including bioluminescence tomography, fluorescence molecular tomography, and Cerenkov luminescence tomography. He has developed new artificial intelligence strategies for medical imaging big data analysis in the field of Radiomics, and played a major role in establishing a standardized Radiomics database with more than 100,000 cancer patients data collected from over 50 hospitals all over China. He has received numerous awards, including five national top awards for his outstanding work in medical imaging and biometrics recognition.

Affiliations and Expertise

CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, China

Di Dong

Dr. Di Dong is currently an associate professor of Institute of Automation, Chinese Academy of Sciences. He received his Ph.D. degree in Pattern Recognition and Intelligent Systems from Institute of Automation, Chinese Academy of Sciences, China, in 2013. Dr. Dong is the member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences, the active member of AACR (American Association for Cancer Research), and the corresponding member of ESR (European Society of Radiology). Dr. Dong has carried out long-term research work in the field of tumor radiomics and medical big data analysis. In recent years, Dr. Dong has published nearly 50 peer-reviewed SCI journal papers, e.g. Annals of Oncology, European Respiratory Journal, Clinical Cancer Research (3 publications), BMC Medicine, etc. These articles received over 1,600 Google Scholar citations (H-index 24). He has 6 ESI highly cited papers. He has applied for more than 20 patents and 10 software copyright applications in China.

Affiliations and Expertise

Associate Professor, Institute of Automation, Chinese Academy of Sciences, China

Zhenyu Liu

Dr. Zhenyu Liu is currently a professor at CAS Key Laboratory of Molecular Imaging, Institute of Automation. He received his Ph.D. degree in Pattern Recognition and Intelligent Systems from Institute of Automation, Chinese Academy of Sciences, China, in 2014. Dr. Liu got the outstanding youth fund of the Natural Science Foundation of China (NSFC) and is the member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences. His research focuses on the medical imaging analysis, especially the radiomics and its application in oncology research. In recent years, Dr. Liu has published nearly 30 peer-reviewed journal papers, e.g. Clinical Cancer Research, Theranostics, EBioMedicine, Radiotherapy and Oncology, and etc. These articles received over 1,300 Google Scholar citations. He also holds more than 10 patents in China

Affiliations and Expertise

Professor, CAS Key Laboratory of Molecular Imaging, Institute of Automation, China

Jingwei Wei

Dr. Zhenyu Liu is currently a professor at CAS Key Laboratory of Molecular Imaging, Institute of Automation. He received his Ph.D. degree in Pattern Recognition and Intelligent Systems from Institute of Automation, Chinese Academy of Sciences, China, in 2014. Dr. Liu got the outstanding youth fund of the Natural Science Foundation of China (NSFC) and is the member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences. His research focuses on the medical imaging analysis, especially the radiomics and its application in oncology research. In recent years, Dr. Liu has published nearly 30 peer-reviewed journal papers, e.g. Clinical Cancer Research, Theranostics, EBioMedicine, Radiotherapy and Oncology, and etc. These articles received over 1,300 Google Scholar citations. He also holds more than 10 patents in China.

Affiliations and Expertise

Professor, Institute of Automation, Chinese Academy of Sciences, China

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