These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
178 related articles for article (PubMed ID: 32654153)
1. CT-based multi-organ segmentation using a 3D self-attention U-net network for pancreatic radiotherapy. Liu Y; Lei Y; Fu Y; Wang T; Tang X; Jiang X; Curran WJ; Liu T; Patel P; Yang X Med Phys; 2020 Sep; 47(9):4316-4324. PubMed ID: 32654153 [TBL] [Abstract][Full Text] [Related]
2. Head and neck multi-organ auto-segmentation on CT images aided by synthetic MRI. Liu Y; Lei Y; Fu Y; Wang T; Zhou J; Jiang X; McDonald M; Beitler JJ; Curran WJ; Liu T; Yang X Med Phys; 2020 Sep; 47(9):4294-4302. PubMed ID: 32648602 [TBL] [Abstract][Full Text] [Related]
3. Synthetic CT-aided multiorgan segmentation for CBCT-guided adaptive pancreatic radiotherapy. Dai X; Lei Y; Wynne J; Janopaul-Naylor J; Wang T; Roper J; Curran WJ; Liu T; Patel P; Yang X Med Phys; 2021 Nov; 48(11):7063-7073. PubMed ID: 34609745 [TBL] [Abstract][Full Text] [Related]
4. Weaving attention U-net: A novel hybrid CNN and attention-based method for organs-at-risk segmentation in head and neck CT images. Zhang Z; Zhao T; Gay H; Zhang W; Sun B Med Phys; 2021 Nov; 48(11):7052-7062. PubMed ID: 34655077 [TBL] [Abstract][Full Text] [Related]
5. Abdomen CT multi-organ segmentation using token-based MLP-Mixer. Pan S; Chang CW; Wang T; Wynne J; Hu M; Lei Y; Liu T; Patel P; Roper J; Yang X Med Phys; 2023 May; 50(5):3027-3038. PubMed ID: 36463516 [TBL] [Abstract][Full Text] [Related]
6. Automated left ventricular myocardium segmentation using 3D deeply supervised attention U-net for coronary computed tomography angiography; CT myocardium segmentation. Jun Guo B; He X; Lei Y; Harms J; Wang T; Curran WJ; Liu T; Jiang Zhang L; Yang X Med Phys; 2020 Apr; 47(4):1775-1785. PubMed ID: 32017118 [TBL] [Abstract][Full Text] [Related]
7. ARPM-net: A novel CNN-based adversarial method with Markov random field enhancement for prostate and organs at risk segmentation in pelvic CT images. Zhang Z; Zhao T; Gay H; Zhang W; Sun B Med Phys; 2021 Jan; 48(1):227-237. PubMed ID: 33151620 [TBL] [Abstract][Full Text] [Related]
8. Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT. Jiang J; Hong J; Tringale K; Reyngold M; Crane C; Tyagi N; Veeraraghavan H Med Phys; 2023 Aug; 50(8):4758-4774. PubMed ID: 37265185 [TBL] [Abstract][Full Text] [Related]
9. 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]
10. Evaluating the clinical acceptability of deep learning contours of prostate and organs-at-risk in an automated prostate treatment planning process. Duan J; Bernard M; Downes L; Willows B; Feng X; Mourad WF; St Clair W; Chen Q Med Phys; 2022 Apr; 49(4):2570-2581. PubMed ID: 35147216 [TBL] [Abstract][Full Text] [Related]
11. A method of rapid quantification of patient-specific organ doses for CT using deep-learning-based multi-organ segmentation and GPU-accelerated Monte Carlo dose computing. Peng Z; Fang X; Yan P; Shan H; Liu T; Pei X; Wang G; Liu B; Kalra MK; Xu XG Med Phys; 2020 Jun; 47(6):2526-2536. PubMed ID: 32155670 [TBL] [Abstract][Full Text] [Related]
12. A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy. Li Z; Zhu Q; Zhang L; Yang X; Li Z; Fu J Radiat Oncol; 2022 Sep; 17(1):152. PubMed ID: 36064571 [TBL] [Abstract][Full Text] [Related]
13. 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]
14. Auto-segmentation of important centers of growth in the pediatric skeleton to consider during radiation therapy based on deep learning. Qiu W; Zhang W; Ma X; Kong Y; Shi P; Fu M; Wang D; Hu M; Zhou X; Dong Q; Zhou Q; Zhu J Med Phys; 2023 Jan; 50(1):284-296. PubMed ID: 36047281 [TBL] [Abstract][Full Text] [Related]
15. 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]
16. ThoraxNet: a 3D U-Net based two-stage framework for OAR segmentation on thoracic CT images. Francis S; Jayaraj PB; Pournami PN; Thomas M; Jose AT; Binu AJ; Puzhakkal N Phys Eng Sci Med; 2022 Mar; 45(1):189-203. PubMed ID: 35029804 [TBL] [Abstract][Full Text] [Related]
17. Machine-assisted interpolation algorithm for semi-automated segmentation of highly deformable organs. Luximon DC; Abdulkadir Y; Chow PE; Morris ED; Lamb JM Med Phys; 2022 Jan; 49(1):41-51. PubMed ID: 34783027 [TBL] [Abstract][Full Text] [Related]
18. Synthetic MRI-aided multi-organ segmentation on male pelvic CT using cycle consistent deep attention network. Dong X; Lei Y; Tian S; Wang T; Patel P; Curran WJ; Jani AB; Liu T; Yang X Radiother Oncol; 2019 Dec; 141():192-199. PubMed ID: 31630868 [TBL] [Abstract][Full Text] [Related]
19. Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer. Ahn SH; Yeo AU; Kim KH; Kim C; Goh Y; Cho S; Lee SB; Lim YK; Kim H; Shin D; Kim T; Kim TH; Youn SH; Oh ES; Jeong JH Radiat Oncol; 2019 Nov; 14(1):213. PubMed ID: 31775825 [TBL] [Abstract][Full Text] [Related]
20. Fully automated multiorgan segmentation in abdominal magnetic resonance imaging with deep neural networks. Chen Y; Ruan D; Xiao J; Wang L; Sun B; Saouaf R; Yang W; Li D; Fan Z Med Phys; 2020 Oct; 47(10):4971-4982. PubMed ID: 32748401 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]