232 related articles for article (PubMed ID: 33117694)
1. Evaluation of Automatic Segmentation Model With Dosimetric Metrics for Radiotherapy of Esophageal Cancer.
Zhu J; Chen X; Yang B; Bi N; Zhang T; Men K; Dai J
Front Oncol; 2020; 10():564737. PubMed ID: 33117694
[No Abstract] [Full Text] [Related]
2. Geometric and Dosimetric Evaluation of the Automatic Delineation of Organs at Risk (OARs) in Non-Small-Cell Lung Cancer Radiotherapy Based on a Modified DenseNet Deep Learning Network.
Zhang F; Wang Q; Yang A; Lu N; Jiang H; Chen D; Yu Y; Wang Y
Front Oncol; 2022; 12():861857. PubMed ID: 35371991
[TBL] [Abstract][Full Text] [Related]
3. The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer.
Guo H; Wang J; Xia X; Zhong Y; Peng J; Zhang Z; Hu W
Radiat Oncol; 2021 Jun; 16(1):113. PubMed ID: 34162410
[TBL] [Abstract][Full Text] [Related]
4. Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery.
Chung SY; Chang JS; Choi MS; Chang Y; Choi BS; Chun J; Keum KC; Kim JS; Kim YB
Radiat Oncol; 2021 Feb; 16(1):44. PubMed ID: 33632248
[TBL] [Abstract][Full Text] [Related]
5. Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.
Kawula M; Purice D; Li M; Vivar G; Ahmadi SA; Parodi K; Belka C; Landry G; Kurz C
Radiat Oncol; 2022 Jan; 17(1):21. PubMed ID: 35101068
[TBL] [Abstract][Full Text] [Related]
6. Clinical evaluation on automatic segmentation results of convolutional neural networks in rectal cancer radiotherapy.
Li J; Song Y; Wu Y; Liang L; Li G; Bai S
Front Oncol; 2023; 13():1158315. PubMed ID: 37731629
[TBL] [Abstract][Full Text] [Related]
7. The predictive value of segmentation metrics on dosimetry in organs at risk of the brain.
Poel R; Rüfenacht E; Hermann E; Scheib S; Manser P; Aebersold DM; Reyes M
Med Image Anal; 2021 Oct; 73():102161. PubMed ID: 34293536
[TBL] [Abstract][Full Text] [Related]
8. Geometric and dosimetric evaluation of deep learning based auto-segmentation for clinical target volume on breast cancer.
Zhong Y; Guo Y; Fang Y; Wu Z; Wang J; Hu W
J Appl Clin Med Phys; 2023 Jul; 24(7):e13951. PubMed ID: 36920901
[TBL] [Abstract][Full Text] [Related]
9. Automatic multiorgan segmentation in thorax CT images using U-net-GAN.
Dong X; Lei Y; Wang T; Thomas M; Tang L; Curran WJ; Liu T; Yang X
Med Phys; 2019 May; 46(5):2157-2168. PubMed ID: 30810231
[TBL] [Abstract][Full Text] [Related]
10. Segmentation of organs-at-risk in cervical cancer CT images with a convolutional neural network.
Liu Z; Liu X; Xiao B; Wang S; Miao Z; Sun Y; Zhang F
Phys Med; 2020 Jan; 69():184-191. PubMed ID: 31918371
[TBL] [Abstract][Full Text] [Related]
11. Geometric and Dosimetric Evaluation of Deep Learning-Based Automatic Delineation on CBCT-Synthesized CT and Planning CT for Breast Cancer Adaptive Radiotherapy: A Multi-Institutional Study.
Dai Z; Zhang Y; Zhu L; Tan J; Yang G; Zhang B; Cai C; Jin H; Meng H; Tan X; Jian W; Yang W; Wang X
Front Oncol; 2021; 11():725507. PubMed ID: 34858813
[TBL] [Abstract][Full Text] [Related]
12. A Feasibility Study of Deep Learning-Based Auto-Segmentation Directly Used in VMAT Planning Design and Optimization for Cervical Cancer.
Chen A; Chen F; Li X; Zhang Y; Chen L; Chen L; Zhu J
Front Oncol; 2022; 12():908903. PubMed ID: 35719942
[TBL] [Abstract][Full Text] [Related]
13. Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric Evaluation.
van Rooij W; Dahele M; Ribeiro Brandao H; Delaney AR; Slotman BJ; Verbakel WF
Int J Radiat Oncol Biol Phys; 2019 Jul; 104(3):677-684. PubMed ID: 30836167
[TBL] [Abstract][Full Text] [Related]
14. Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.
Zhang T; Yang Y; Wang J; Men K; Wang X; Deng L; Bi N
Medicine (Baltimore); 2020 Aug; 99(34):e21800. PubMed ID: 32846816
[TBL] [Abstract][Full Text] [Related]
15. A Preliminary Experience of Implementing Deep-Learning Based Auto-Segmentation in Head and Neck Cancer: A Study on Real-World Clinical Cases.
Zhong Y; Yang Y; Fang Y; Wang J; Hu W
Front Oncol; 2021; 11():638197. PubMed ID: 34026615
[TBL] [Abstract][Full Text] [Related]
16. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
Tong N; Gou S; Yang S; Ruan D; Sheng K
Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
[TBL] [Abstract][Full Text] [Related]
17. Assessment of Monte Carlo algorithm for compliance with RTOG 0915 dosimetric criteria in peripheral lung cancer patients treated with stereotactic body radiotherapy.
Pokhrel D; Sood S; Badkul R; Jiang H; McClinton C; Lominska C; Kumar P; Wang F
J Appl Clin Med Phys; 2016 May; 17(3):277-293. PubMed ID: 27167284
[TBL] [Abstract][Full Text] [Related]
18. Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods.
Vrtovec T; Močnik D; Strojan P; Pernuš F; Ibragimov B
Med Phys; 2020 Sep; 47(9):e929-e950. PubMed ID: 32510603
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer.
Wang J; Chen Y; Xie H; Luo L; Tang Q
Sci Rep; 2022 Aug; 12(1):13650. PubMed ID: 35953516
[TBL] [Abstract][Full Text] [Related]
20. Clinical Validation and Treatment Plan Evaluation Based on Autodelineation of the Clinical Target Volume for Prostate Cancer Radiotherapy.
Shen J; Tao Y; Guan H; Zhen H; He L; Dong T; Wang S; Chen Y; Chen Q; Liu Z; Zhang F
Technol Cancer Res Treat; 2023; 22():15330338231164883. PubMed ID: 36991566
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
