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Auto-Segmentation for Radiation Oncology State Of the Art



This book provides a comprehensive introduction to current state-of-the-art auto-segmentation approaches used in radiation oncology for auto-delineation of organs-of-risk for thoracic radiation treatment planning. Containing the latest, cutting edge technologies and treatments, it explores 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 and discusses the impact of the different algorithm modules to the algorithm performance as well as the implementation issues for clinical use (including data curation challenges and auto-contour evaluations).

This book is an ideal guide for radiation oncology centers looking to learn more about potential auto-segmentation tools for their clinic in addition to medical physicists commissioning auto-segmentation for clinical use.

Features:

Up-to-date with the latest technologies in the field
Edited by leading authorities in the area, with chapter contributions from subject area specialists
All approaches presented in this book are validated using a standard benchmark dataset established by the Thoracic Auto-segmentation Challenge held as an event of the 2017 Annual Meeting of American Association of Physicists in Medicine

https://www.routledge.com/


Ketersediaan

B6238/2023/24616.994 YAN APERPUSTAKAAN BAPETEN (600)Tersedia

Informasi Detil

Judul Seri
-
No. Panggil
616.994 YAN A
Penerbit CRC Press : Boca Raton.,
Deskripsi Fisik
253p. : illus. ; 24 cm
Bahasa
English
ISBN/ISSN
978-0-429-32378-2
Klasifikasi
616.994
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
-
Subyek
Info Detil Spesifik
-
Pernyataan Tanggungjawab

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JudulEdisiBahasa
Radiation Oncology (3rd Edition): A Question-Based Reviewen

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