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Acta Oncologica Volume 59, 2020 - Issue 8
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ORIGINAL ARTICLES: RADIOTHERAPY AND RADIOBIOLOGY

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples

Zhongjian JuDepartment of Radiation Oncology, The First Medical Center of People’s Liberation Army General Hospital, Beijing, China; View further author information
,
Qingnan WuDepartment of Radiation Therapy, Peking University International Hospital, Beijing, China; View further author information
,
Wei YangDepartment of Radiation Oncology, The First Medical Center of People’s Liberation Army General Hospital, Beijing, China; View further author information
,
Shanshan GuDepartment of Radiation Oncology, The First Medical Center of People’s Liberation Army General Hospital, Beijing, China; View further author information
,
Wen GuoSchool of Physics Science and Technology, Wuhan University, Wuhan, China; View further author information
,
Jinyuan WangDepartment of Radiation Oncology, The First Medical Center of People’s Liberation Army General Hospital, Beijing, China; View further author information
,
Ruigang GeDepartment of Radiation Oncology, The First Medical Center of People’s Liberation Army General Hospital, Beijing, China; View further author information
,
Hong QuanSchool of Physics Science and Technology, Wuhan University, Wuhan, China; View further author information
,
Jie LiuBeijing Eastraycloud Technology Inc, Beijing, ChinaView further author information
&
Baolin QuDepartment of Radiation Oncology, The First Medical Center of People’s Liberation Army General Hospital, Beijing, China; Correspondence[email protected]
View further author information
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Pages 933-939 | Received 19 Mar 2020, Accepted 23 May 2020, Published online: 22 Jun 2020

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Iva VilasBoas-Ribeiro, Martine Franckena, Gerard C. van Rhoon, Juan A. Hernández-Tamames & Margarethus M. Paulides. (2023) Using MRI to measure position and anatomy changes and assess their impact on the accuracy of hyperthermia treatment planning for cervical cancer. International Journal of Hyperthermia 40:1.
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Articles from other publishers (11)

Liang Jiang, Jiarui Sun, Yajing Wang, Haodi Yang, Yu-Chen Chen, Mingyang Peng, Hong Zhang, Yang Chen & Xindao Yin. (2024) Diffusion-/perfusion-weighted imaging fusion to automatically identify stroke within 4.5 h. European Radiology.
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Xianan Li, Lecheng Jia, Fengyu Lin, Fan Chai, Tao Liu, Wei Zhang, Ziquan Wei, Weiqi Xiong, Hua Li, Min Zhang & Yi Wang. (2024) Semi‐supervised auto‐segmentation method for pelvic organ‐at‐risk in magnetic resonance images based on deep‐learning. Journal of Applied Clinical Medical Physics 25:3.
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Lorenza Bonaldi, Andrea Pretto, Carmelo Pirri, Francesca Uccheddu, Chiara Giulia Fontanella & Carla Stecco. (2023) Deep Learning-Based Medical Images Segmentation of Musculoskeletal Anatomical Structures: A Survey of Bottlenecks and Strategies. Bioengineering 10:2, pages 137.
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Chongze Yang, Lan-hui Qin, Yu-en Xie & Jin-yuan Liao. (2022) Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis. Radiation Oncology 17:1.
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Ching-Wei Wang, Muhammad-Adil Khalil & Nabila Firdi. (2022) A Survey on Deep Learning for Precision Oncology. Diagnostics 12:6, pages 1489.
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Along Chen, Fei Chen, Xiaofang Li, Yazhi Zhang, Li Chen, Lixin Chen & Jinhan Zhu. (2022) A Feasibility Study of Deep Learning-Based Auto-Segmentation Directly Used in VMAT Planning Design and Optimization for Cervical Cancer. Frontiers in Oncology 12.
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Ahmed Tamer Salah, Mostafa Abd-Elaziz, Muhammed Ibrahim Abbas, Youssef Hesham Sayed, Zeyad Mohammed Elsahaer, M.M. Eissa, Soha Ahmed & Ghada Ahmed Khoriba. (2022) Multi-Organ Auto-segmentation using Deep Learning approaches for head and neck section for Cancer treatment. Multi-Organ Auto-segmentation using Deep Learning approaches for head and neck section for Cancer treatment.
Seenia Francis, Harsh Bagaria, Jayaraj P B, Pournami P N & Niyas Puzhakkal. (2022) Auto Contouring of OAR in Pelvic CT Images Using an Encoder-Decoder Based Deep Residual Network. Auto Contouring of OAR in Pelvic CT Images Using an Encoder-Decoder Based Deep Residual Network.
Yi Ding, Zhiran Chen, Ziqi Wang, Xiaohong Wang, Desheng Hu, Pingping Ma, Chi Ma, Wei Wei, Xiangbin Li, Xudong Xue & Xiao Wang. (2022) Three‐dimensional deep neural network for automatic delineation of cervical cancer in planning computed tomography images. Journal of Applied Clinical Medical Physics 23:4.
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Marta Casati, Stefano Piffer, Silvia Calusi, Livia Marrazzo, Gabriele Simontacchi, Vanessa Di Cataldo, Daniela Greto, Isacco Desideri, Marco Vernaleone, Giulio Francolini, Lorenzo Livi & Stefania Pallotta. (2022) Clinical validation of an automatic atlas‐based segmentation tool for male pelvis CT images. Journal of Applied Clinical Medical Physics 23:3.
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Seung Yeon Shin, Sungwon Lee & Ronald M. Summers. 2021. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 282 292 .

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