122 related articles for article (PubMed ID: 35041597)
1. NPCNet: Jointly Segment Primary Nasopharyngeal Carcinoma Tumors and Metastatic Lymph Nodes in MR Images.
Li Y; Dan T; Li H; Chen J; Peng H; Liu L; Cai H
IEEE Trans Med Imaging; 2022 Jul; 41(7):1639-1650. PubMed ID: 35041597
[TBL] [Abstract][Full Text] [Related]
2. SeqSeg: A sequential method to achieve nasopharyngeal carcinoma segmentation free from background dominance.
Tao G; Li H; Huang J; Han C; Chen J; Ruan G; Huang W; Hu Y; Dan T; Zhang B; He S; Liu L; Cai H
Med Image Anal; 2022 May; 78():102381. PubMed ID: 35231849
[TBL] [Abstract][Full Text] [Related]
3. Multiscale Local Enhancement Deep Convolutional Networks for the Automated 3D Segmentation of Gross Tumor Volumes in Nasopharyngeal Carcinoma: A Multi-Institutional Dataset Study.
Yang G; Dai Z; Zhang Y; Zhu L; Tan J; Chen Z; Zhang B; Cai C; He Q; Li F; Wang X; Yang W
Front Oncol; 2022; 12():827991. PubMed ID: 35387126
[TBL] [Abstract][Full Text] [Related]
4. WET-UNet: Wavelet integrated efficient transformer networks for nasopharyngeal carcinoma tumor segmentation.
Zeng Y; Li J; Zhao Z; Liang W; Zeng P; Shen S; Zhang K; Shen C
Sci Prog; 2024; 107(2):368504241232537. PubMed ID: 38567422
[TBL] [Abstract][Full Text] [Related]
5. Lightweight Compound Scaling Network for Nasopharyngeal Carcinoma Segmentation from MR Images.
Liu Y; Han G; Liu X
Sensors (Basel); 2022 Aug; 22(15):. PubMed ID: 35957432
[TBL] [Abstract][Full Text] [Related]
6. Risk factors and distribution features of level IB lymph nodes metastasis in nasopharyngeal carcinoma.
Zeng L; Zhang Q; Ao F; Jiang CL; Xiao Y; Xie HH; Tang YQ; Gong XC; Li JG
Auris Nasus Larynx; 2019 Jun; 46(3):457-464. PubMed ID: 30528104
[TBL] [Abstract][Full Text] [Related]
7. Distribution pattern and prognosis of metastatic lymph nodes in cervical posterior to level V in nasopharyngeal carcinoma patients.
Jiang C; Gao H; Zhang L; Li H; Zhang T; Ma J; Liu B
BMC Cancer; 2020 Jul; 20(1):667. PubMed ID: 32680466
[TBL] [Abstract][Full Text] [Related]
8. A Collaborative Dictionary Learning Model for Nasopharyngeal Carcinoma Segmentation on Multimodalities MR Sequences.
Wang H; Han G; Li H; Tao G; Zhuo E; Liu L; Cai H; Ou Y
Comput Math Methods Med; 2020; 2020():7562140. PubMed ID: 32908581
[TBL] [Abstract][Full Text] [Related]
9. Nasopharyngeal carcinoma segmentation using a region growing technique.
Chanapai W; Bhongmakapat T; Tuntiyatorn L; Ritthipravat P
Int J Comput Assist Radiol Surg; 2012 May; 7(3):413-22. PubMed ID: 21671094
[TBL] [Abstract][Full Text] [Related]
10. MRF-RFS: A Modified Random Forest Recursive Feature Selection Algorithm for Nasopharyngeal Carcinoma Segmentation.
Fei Y; Zhang F; Zu C; Hong M; Peng X; Xiao J; Wu X; Zhou J; Wang Y
Methods Inf Med; 2020 Aug; 59(4-05):151-161. PubMed ID: 33618420
[TBL] [Abstract][Full Text] [Related]
11. The value of detailed MR imaging report of primary tumor and lymph nodes on prognostic nomograms for nasopharyngeal carcinoma after intensity-modulated radiotherapy.
Wan Y; Tian L; Zhang G; Xin H; Li H; Dong A; Liang Y; Jing B; Zhou J; Cui C; Chen M; Sun Y; Xie C; Liu L; Shao Y
Radiother Oncol; 2019 Feb; 131():35-44. PubMed ID: 30773185
[TBL] [Abstract][Full Text] [Related]
12. Is unenhanced 18F-FDG-PET/CT better than enhanced CT in the detection of retropharyngeal lymph node metastasis in nasopharyngeal carcinoma?
Wu IS; Hung GU; Chang BL; Liu CK; Chang TH; Lee HS; Chen MK
Ear Nose Throat J; 2016; 95(4-5):178-84. PubMed ID: 27140019
[TBL] [Abstract][Full Text] [Related]
13. Computer-aided diagnosis and regional segmentation of nasopharyngeal carcinoma based on multi-modality medical images.
Qi Y; Li J; Chen H; Guo Y; Yin Y; Gong G; Wang L
Int J Comput Assist Radiol Surg; 2021 Jun; 16(6):871-882. PubMed ID: 33782844
[TBL] [Abstract][Full Text] [Related]
14. DeepMTS: Deep Multi-Task Learning for Survival Prediction in Patients With Advanced Nasopharyngeal Carcinoma Using Pretreatment PET/CT.
Meng M; Gu B; Bi L; Song S; Feng DD; Kim J
IEEE J Biomed Health Inform; 2022 Sep; 26(9):4497-4507. PubMed ID: 35696469
[TBL] [Abstract][Full Text] [Related]
15. (68)Ga-DOTA-peptide: A novel molecular biomarker for nasopharyngeal carcinoma.
Khor LK; Loi HY; Sinha AK; Tong KT; Goh BC; Loh KS; Lu SJ
Head Neck; 2016 Apr; 38(4):E76-80. PubMed ID: 26275126
[TBL] [Abstract][Full Text] [Related]
16. 3D segmentation of nasopharyngeal carcinoma from CT images using cascade deep learning.
Daoud B; Morooka K; Kurazume R; Leila F; Mnejja W; Daoud J
Comput Med Imaging Graph; 2019 Oct; 77():101644. PubMed ID: 31426004
[TBL] [Abstract][Full Text] [Related]
17. Nasopharyngeal carcinoma segmentation based on enhanced convolutional neural networks using multi-modal metric learning.
Ma Z; Zhou S; Wu X; Zhang H; Yan W; Sun S; Zhou J
Phys Med Biol; 2019 Jan; 64(2):025005. PubMed ID: 30524024
[TBL] [Abstract][Full Text] [Related]
18. Delineation of Neck Clinical Target Volume Specific to Nasopharyngeal Carcinoma Based on Lymph Node Distribution and the International Consensus Guidelines.
Lin L; Lu Y; Wang XJ; Chen H; Yu S; Tian J; Zhou GQ; Zhang LL; Qi ZY; Hu J; Ma J; Sun Y
Int J Radiat Oncol Biol Phys; 2018 Mar; 100(4):891-902. PubMed ID: 29485068
[TBL] [Abstract][Full Text] [Related]
19. [Role of 18F-FDG PET/CT in diagnosis and staging of nasopharyngeal carcinoma].
Lin XP; Zhao C; Chen MY; Fan W; Zhang X; Zhi SF; Liang PY
Ai Zheng; 2008 Sep; 27(9):974-8. PubMed ID: 18799039
[TBL] [Abstract][Full Text] [Related]
20. Clinical treatment considerations in the intensity-modulated radiotherapy era for patients with N0-category nasopharyngeal carcinoma and enlarged neck lymph nodes.
Peng H; Chen L; Guo R; Zhang Y; Li WF; Mao YP; Sun Y; Zhang F; Liu LZ; Tian L; Ma J
Chin J Cancer; 2017 Mar; 36(1):32. PubMed ID: 28340596
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
