AI-Augmented Images for X-Ray Guiding Radiation Therapy Delivery

Tianye Niu; Tiffany Tsui; Wei Zhao

doi:10.1016/j.semradonc.2022.06.006

AI-Augmented Images for X-Ray Guiding Radiation Therapy Delivery

Tianye Niu^*
, Tiffany Tsui
, Wei Zhao

^*Corresponding author for this work

School of Physics

Shenzhen Bay Laboratory
Georgia Institute of Technology

Research output: Contribution to journal › Review article › peer-review

3 Scopus citations

Abstract

Cancer accounts for nearly 10 million deaths in 2020 and is a leading cause of death worldwide. Radiation therapy is an effective modality to cure cancer. The ultimate goal of successful radiation therapy is to accurately deliver a safe and therapeutic dose of radiation to cancerous target cells while limiting radiation to the healthy tissue in the beam pathway and the surrounding normal tissue. With advancing radiation treatment technology, better imaging techniques are imperative for safe, high-dose delivery. Artificial intelligence developments on image-guided radiation therapy technologies, which range from Kilovoltage and Megavoltage modalities to two-dimensional and three-dimensional techniques, are discussed in depth.

Original language	English
Pages (from-to)	365-376
Number of pages	12
Journal	Seminars in Radiation Oncology
Volume	32
Issue number	4
DOIs	https://doi.org/10.1016/j.semradonc.2022.06.006
State	Published - Oct 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1016/j.semradonc.2022.06.006

Cite this

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title = "AI-Augmented Images for X-Ray Guiding Radiation Therapy Delivery",

abstract = "Cancer accounts for nearly 10 million deaths in 2020 and is a leading cause of death worldwide. Radiation therapy is an effective modality to cure cancer. The ultimate goal of successful radiation therapy is to accurately deliver a safe and therapeutic dose of radiation to cancerous target cells while limiting radiation to the healthy tissue in the beam pathway and the surrounding normal tissue. With advancing radiation treatment technology, better imaging techniques are imperative for safe, high-dose delivery. Artificial intelligence developments on image-guided radiation therapy technologies, which range from Kilovoltage and Megavoltage modalities to two-dimensional and three-dimensional techniques, are discussed in depth.",

author = "Tianye Niu and Tiffany Tsui and Wei Zhao",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier Inc.",

year = "2022",

month = oct,

doi = "10.1016/j.semradonc.2022.06.006",

language = "英语",

volume = "32",

pages = "365--376",

journal = "Seminars in Radiation Oncology",

issn = "1053-4296",

publisher = "W.B. Saunders",

number = "4",

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TY - JOUR

T1 - AI-Augmented Images for X-Ray Guiding Radiation Therapy Delivery

AU - Niu, Tianye

AU - Tsui, Tiffany

AU - Zhao, Wei

PY - 2022/10

Y1 - 2022/10

N2 - Cancer accounts for nearly 10 million deaths in 2020 and is a leading cause of death worldwide. Radiation therapy is an effective modality to cure cancer. The ultimate goal of successful radiation therapy is to accurately deliver a safe and therapeutic dose of radiation to cancerous target cells while limiting radiation to the healthy tissue in the beam pathway and the surrounding normal tissue. With advancing radiation treatment technology, better imaging techniques are imperative for safe, high-dose delivery. Artificial intelligence developments on image-guided radiation therapy technologies, which range from Kilovoltage and Megavoltage modalities to two-dimensional and three-dimensional techniques, are discussed in depth.

AB - Cancer accounts for nearly 10 million deaths in 2020 and is a leading cause of death worldwide. Radiation therapy is an effective modality to cure cancer. The ultimate goal of successful radiation therapy is to accurately deliver a safe and therapeutic dose of radiation to cancerous target cells while limiting radiation to the healthy tissue in the beam pathway and the surrounding normal tissue. With advancing radiation treatment technology, better imaging techniques are imperative for safe, high-dose delivery. Artificial intelligence developments on image-guided radiation therapy technologies, which range from Kilovoltage and Megavoltage modalities to two-dimensional and three-dimensional techniques, are discussed in depth.

UR - https://www.scopus.com/pages/publications/85135198561

U2 - 10.1016/j.semradonc.2022.06.006

DO - 10.1016/j.semradonc.2022.06.006

M3 - 文献综述

C2 - 36202439

AN - SCOPUS:85135198561

SN - 1053-4296

VL - 32

SP - 365

EP - 376

JO - Seminars in Radiation Oncology

JF - Seminars in Radiation Oncology

IS - 4

ER -

AI-Augmented Images for X-Ray Guiding Radiation Therapy Delivery

Abstract

UN SDGs

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