{"product_id":"radiomics-and-radiogenomics-9780815375852","title":"Radiomics and Radiogenomics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eRadiomics 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.\u003c\/p\u003e\u003cb\u003e\u003ci\u003e\u003c\/i\u003e\u003c\/b\u003e\u003cp\u003eFeatures\u003c\/p\u003e\u003cul\u003e\n\u003cp\u003e\u003c\/p\u003e\n\u003cli\u003eProvides a first complete overview of the technical underpinnings and clinical applications of radiomics and radiogenomics\u003c\/li\u003e\n\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\"Despite an abundance of research papers and some review articles, there have not been many comprehensive books devoted to these special audiences. Two first‐edition books published in 2019 by the Taylor and Francis Group, \u003cem\u003eRadiomics and Radiogenomics\u003c\/em\u003e (edited by Ruijiang Li, Lei Xing, Sandy Napel, and Daniel L. Rubin) and \u003cem\u003eBig Data in Radiation Oncology\u003c\/em\u003e (edited by Jun Deng and Lei Xing), have opportunely filled this void, and provided a comprehensive review as well as valuable insights on these key new advances. .... From these two books, readers can gain a fundamental understanding of radiomic feature definition and computation, processing steps (such as voxel resampling, MRI field bias correction and normalization, and other data harmonization), and processing parameters (such as fixed bin size vs fixed bin number and voxel neighborhood size). Readers can also develop a deeper appreciation of proper data management in modeling from both texts. As such, the technical knowledge from the books can assist researchers in optimizing their own study design.\"\u003cbr\u003e-Dandan Zheng, in the \u003cem\u003eJournal of Applied Clinical Medical Physics\u003c\/em\u003e, July 2020\u003c\/p\u003e\n\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003ePart I: Introduction\u003c\/strong\u003e \u003c\/p\u003e\n\u003cp\u003e1. Principles and rationale of radiomics and radiogenomics\u003ci\u003e \u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e\u003ci\u003eSandy Napel\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003ePart II: Technical Basis\u003c\/b\u003e\u003c\/p\u003e\n\u003cp\u003e2. Imaging informatics: an overview\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eAssaf Hoogi, Daniel Rubin\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e3. Quantitative imaging using CT\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eLin Lu, Lawrence H. Schwartz, Binsheng Zhao\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e4. Quantitative PET\/CT for radiomics\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eStephen R. Bowen, Paul E. Kinahan, George A. Sandison, Matthew J. Nyflot\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e5. Common techniques of quantitative MRI\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eDavid Hormuth II, Jack Virostko, Ashley Stokes, Adrienne Dula, Anna G. Sorace, Jennifer G. Whisenant, Jared Weis, C. Chad Quarles, Michael I. Miga, Thomas E. Yankeelov\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e6. Tumor segmentation\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eSpyridon Bakas, Rhea Chitalia, Despina Kontos, Yong Fan, Christos Davatzikos\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e7. Habitat imaging of tumor evolution by magnetic resonance imaging (MRI\u003cem\u003e) \u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eBruna Victorasso Jardim-Perassi, Gary Martinez, Robert Gillies\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e8. Feature extraction and qualification\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eLise Wei, Issam El Naqa\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e9. Predictive modeling, machine learning, and statistical issues\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003ePanagiotis Korfiatis, Timothy L. Kline, Zeynettin Akkus, Kenneth Philbrick, Bradley J. Erikson\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e10. Radiogenomics: rationale and methods\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eOlivier Gevaert\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e11. Resources and datasets for radiomics\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eKen Chang, Andrew Beers, James Brown, Jayashree Kalpathy-Cramer\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003ePart III: Clinical Applications\u003c\/b\u003e\u003c\/p\u003e\n\u003cp\u003e12. Roles of radiomics and radiogenomics in clinical practice\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eTianyue Niu, Xiaoli Sun, Pengfei Yang, Guohong Cao, Khin K. Tha, Hiroki Shirato, Kathleen Horst, Lei Xing\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e13. Brain cancer\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eWilliam D. Dunn Jr, Rivka Colen\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e14. Breast cancer\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eHui Li, Maryellen L. Giger\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e15. Lung cancer\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eDong Di, Jie Tian, \u003c\/em\u003eShuo \u003cem\u003eWang\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e16. The essence of R in head and neck cancer\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eHesham Elhalawani, Arvind Rao, Clifton D. Fuller\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e17. Gastrointestinal cancers\u003c\/p\u003e\n\u003cp\u003e\u003ci\u003eZaiyi Liu\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e18. Radiomics in genitourinary cancers: prostate cancer\u003c\/p\u003e\n\u003cp\u003e\u003ci\u003eSatish Viswanath, Anant Madabhushi\u003c\/i\u003e\u003c\/p\u003e\n\u003cp\u003e19. Radiomics analysis for gynecologic cancers\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eHarini Veeraraghavan\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e20. Applications of imaging genomics beyond oncology\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eXiaohui Yao, Jingwen Yan, Li Shen\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003ePart IV: Future Outlook\u003c\/b\u003e\u003c\/p\u003e\n\u003cp\u003e21. Quantitative imaging to guide mechanism based modeling of cancer\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eDavid A. Hormouth II, Matthew T. McKenna, Thomas E. Yankeelov\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e22. Looking Ahead: Opportunities and Challenges in Radiomics and Radiogenomics\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eRuijiang Li, Yan Wu, Michael Gensheimer, Masoud Badiei Khuzani, Lei Xing\u003c\/em\u003e\u003c\/p\u003e\n\u003c\/ul\u003e","brand":"Taylor \u0026 Francis Inc","offers":[{"title":"Default Title","offer_id":50577563877719,"sku":"9780815375852","price":204.25,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780815375852.jpg?v=1746095865","url":"https:\/\/bookcurl.com\/products\/radiomics-and-radiogenomics-9780815375852","provider":"Book Curl","version":"1.0","type":"link"}