{"product_id":"autosegmentation-for-radiation-oncology-state-of-the-art-9780367761226","title":"Auto-Segmentation for Radiation Oncology: State of the Art","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book provides an introduction to state-of-the-art auto-segmentation approaches used in radiation oncology for auto-delineation of organs-of-risk for thoracic radiation treatment planning. It explores deep-learning methods, multi-atlas-based methods, and model-based methods and discusses their impact on algorithm performance and implementation issues. It is an ideal guide for radiation oncology centers and medical physicists looking to learn more about potential auto-segmentation tools. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 256 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 31 May 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThis comprehensive book offers a thorough introduction to the state-of-the-art auto-segmentation approaches used in radiation oncology for the automated delineation of organs-at-risk for thoracic radiation treatment planning. It encompasses the latest, cutting-edge technologies and treatments, delving into deep-learning methods, multi-atlas-based methods, and model-based methods that are currently being developed for clinical radiation oncology applications. Each chapter focuses on a specific aspect of algorithm choices, discussing the impact of different algorithm modules on the algorithm's performance and the implementation challenges for clinical use, including data curation challenges and auto-contour evaluations.\u003cbr\u003e\u003cbr\u003eThis book serves as an invaluable guide for radiation oncology centers seeking to explore potential auto-segmentation tools for their clinics, as well as medical physicists commissioning auto-segmentation for clinical use. It features:\u003cbr\u003e\u003cbr\u003eUp-to-date coverage of the latest technologies in the field, with contributions from renowned authorities in the area.\u003cbr\u003eChapter contributions from subject area specialists, ensuring a diverse and expert perspective.\u003cbr\u003eAll approaches presented in this book are validated using a standardized benchmark dataset established by the Thoracic Auto-segmentation Challenge, held as an event of the 2017 Annual Meeting of the American Association of Physicists in Medicine.\u003cbr\u003e\u003cbr\u003eBy providing a comprehensive exploration of auto-segmentation techniques, this book empowers radiation oncology professionals to stay at the forefront of advancements in the field and improve the accuracy and efficiency of radiation treatment planning. It is a valuable resource for researchers, practitioners, and students alike.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 510g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 254 x 178 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9780367761226\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44272377037050,"sku":"9780367761226","price":47.59,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1685703122271_book.jpg?v=1686252724","url":"https:\/\/shulphink.com\/products\/autosegmentation-for-radiation-oncology-state-of-the-art-9780367761226","provider":"Shulph Ink","version":"1.0","type":"link"}