Automatic delineation of the clinical target volume and organs at risk by deep learning for rectal cancer postoperative radiotherapy

Radiotherapy and Oncology ◽

10.1016/j.radonc.2020.01.020 ◽

2020 ◽

Vol 145 ◽

pp. 186-192 ◽

Author(s):

Ying Song ◽

Junjie Hu ◽

Qiang Wu ◽

Feng Xu ◽

Shihong Nie ◽

...

Keyword(s):

At Risk ◽

Rectal Cancer ◽

Deep Learning ◽

Clinical Target Volume ◽

Organs At Risk ◽

Postoperative Radiotherapy ◽

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Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks

Medical Physics ◽

10.1002/mp.12602 ◽

2017 ◽

Vol 44 (12) ◽

pp. 6377-6389 ◽

Author(s):

Kuo Men ◽

Jianrong Dai ◽

Yexiong Li

Keyword(s):

Neural Networks ◽

At Risk ◽

Rectal Cancer ◽

Convolutional Neural Networks ◽

Clinical Target Volume ◽

Organs At Risk ◽

Automatic Segmentation ◽

Target Volume ◽

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Development and validation of a deep learning algorithm for auto-delineation of clinical target volume and organs at risk in cervical cancer radiotherapy

Radiotherapy and Oncology ◽

10.1016/j.radonc.2020.09.060 ◽

2020 ◽

Vol 153 ◽

pp. 172-179

Author(s):

Zhikai Liu ◽

Xia Liu ◽

Hui Guan ◽

Hongan Zhen ◽

Yuliang Sun ◽

...

Keyword(s):

Cervical Cancer ◽

At Risk ◽

Deep Learning ◽

Clinical Target Volume ◽

Learning Algorithm ◽

Organs At Risk ◽

Target Volume ◽

Cancer Radiotherapy ◽

Deep Learning Algorithm ◽

Development And Validation

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Evaluation of deep learning‐based auto‐segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients

Journal of Applied Clinical Medical Physics ◽

10.1002/acm2.13097 ◽

2020 ◽

Vol 21 (12) ◽

pp. 272-279

Author(s):

Zhi Wang ◽

Yankui Chang ◽

Zhao Peng ◽

Yin Lv ◽

Weijiong Shi ◽

...

Keyword(s):

Cervical Cancer ◽

At Risk ◽

Deep Learning ◽

Cancer Patients ◽

Clinical Target Volume ◽

Organs At Risk ◽

Target Volume ◽

Segmentation Algorithms

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Automatic segmentation of the clinical target volume and organs at risk for rectal cancer radiotherapy using structure-contextual representations based on 3D high-resolution network

Biomedical Signal Processing and Control ◽

10.1016/j.bspc.2021.103362 ◽

2022 ◽

Vol 73 ◽

pp. 103362

Author(s):

Yiwei Yang ◽

Rui Huang ◽

Guofeng Lv ◽

Zhiqiang Hu ◽

Guoping Shan ◽

...

Keyword(s):

At Risk ◽

Rectal Cancer ◽

High Resolution ◽

Clinical Target Volume ◽

Organs At Risk ◽

Automatic Segmentation ◽

Target Volume ◽

Cancer Radiotherapy

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Development And Validation Of A Deep Learning Algorithm For Auto-Delineation Of Clinical Target Volume And Organs At Risk In Cervical Cancer Radiotherapy

International Journal of Radiation Oncology*Biology*Physics ◽

10.1016/j.ijrobp.2020.07.204 ◽

2020 ◽

Vol 108 (3) ◽

pp. e766

Author(s):

L. Zhikai ◽

H. Guan

Keyword(s):

Cervical Cancer ◽

At Risk ◽

Deep Learning ◽

Clinical Target Volume ◽

Learning Algorithm ◽

Organs At Risk ◽

Target Volume ◽

Cancer Radiotherapy ◽

Deep Learning Algorithm ◽

Development And Validation

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RefineNet-based automatic delineation of the clinical target volume and organs at risk for three-dimensional brachytherapy for cervical cancer

Annals of Translational Medicine ◽

10.21037/atm-21-4074 ◽

2021 ◽

Vol 0 (0) ◽

pp. 0-0

Author(s):

Xue Jiang ◽

Fang Wang ◽

Ying Chen ◽

Senxiang Yan

Keyword(s):

Cervical Cancer ◽

At Risk ◽

Clinical Target Volume ◽

Organs At Risk ◽

Three Dimensional ◽

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Evaluation of Deep Learning-Based Auto-Segmentation of Target Volume and Organs-at-Risk in Breast Cancer Patients

International Journal of Radiation Oncology*Biology*Physics ◽

10.1016/j.ijrobp.2020.07.235 ◽

2020 ◽

Vol 108 (3) ◽

pp. e779

Author(s):

S.Y. Chung ◽

J.S. Chang ◽

Y. Chang ◽

B.S. Choi ◽

J. Chun ◽

...

Keyword(s):

Breast Cancer ◽

At Risk ◽

Deep Learning ◽

Cancer Patients ◽

Organs At Risk ◽

Target Volume ◽

Breast Cancer Patients

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Interobserver variation in clinical target volume and organs at risk segmentation in post-parotidectomy radiotherapy: can segmentation protocols help?

British Journal of Radiology ◽

10.1259/bjr/66693547 ◽

2012 ◽

Vol 85 (1016) ◽

pp. e530-e536 ◽

Author(s):

M Mukesh ◽

R Benson ◽

R Jena ◽

A Hoole ◽

T Roques ◽

...

Keyword(s):

At Risk ◽

Clinical Target Volume ◽

Organs At Risk ◽

Target Volume ◽

Interobserver Variation

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A Comparison of Traditional Versus Response-based Involved-Field Radiation Therapy on Clinical Target Volume and Organs-at-Risk for Pediatric Rapid Early Responders With High-Risk Hodgkin Lymphoma

International Journal of Radiation Oncology*Biology*Physics ◽

10.1016/j.ijrobp.2012.07.1714 ◽

2012 ◽

Vol 84 (3) ◽

pp. S642

Author(s):

J.E. Wilson ◽

M. South ◽

B. Teh ◽

B. Butler ◽

A. Paulino

Keyword(s):

At Risk ◽

Radiation Therapy ◽

High Risk ◽

Hodgkin Lymphoma ◽

Clinical Target Volume ◽

Organs At Risk ◽

Target Volume ◽

Field Radiation ◽

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The Lack of Consensus of International Contouring Guidelines for the Dorsal Border of the Chest Wall Clinical Target Volume: What is the Impact on Organs at Risk and Relationships to Patterns of Recurrence in the Modern Era?

Advances in Radiation Oncology ◽

10.1016/j.adro.2018.09.008 ◽

2019 ◽

Vol 4 (1) ◽

pp. 35-42 ◽

Author(s):

Phillip M. Pifer ◽

Robert P. Bice ◽

Geraldine M. Jacobson ◽

Kristin Lupinacci ◽

Sushil Beriwal ◽

...

Keyword(s):

At Risk ◽

Clinical Target Volume ◽

Organs At Risk ◽

Target Volume ◽

Patterns Of Recurrence ◽

Contouring Guidelines

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