220 related articles for article (PubMed ID: 33544302)
1. Convolutional neural network in nasopharyngeal carcinoma: how good is automatic delineation for primary tumor on a non-contrast-enhanced fat-suppressed T2-weighted MRI?
Wong LM; Ai QYH; Mo FKF; Poon DMC; King AD
Jpn J Radiol; 2021 Jun; 39(6):571-579. PubMed ID: 33544302
[TBL] [Abstract][Full Text] [Related]
2. A convolutional neural network combined with positional and textural attention for the fully automatic delineation of primary nasopharyngeal carcinoma on non-contrast-enhanced MRI.
Wong LM; Ai QYH; Poon DMC; Tong M; Ma BBY; Hui EP; Shi L; King AD
Quant Imaging Med Surg; 2021 Sep; 11(9):3932-3944. PubMed ID: 34476179
[TBL] [Abstract][Full Text] [Related]
3. Convolutional neural network for discriminating nasopharyngeal carcinoma and benign hyperplasia on MRI.
Wong LM; King AD; Ai QYH; Lam WKJ; Poon DMC; Ma BBY; Chan KCA; Mo FKF
Eur Radiol; 2021 Jun; 31(6):3856-3863. PubMed ID: 33241522
[TBL] [Abstract][Full Text] [Related]
4. Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma.
Lin L; Dou Q; Jin YM; Zhou GQ; Tang YQ; Chen WL; Su BA; Liu F; Tao CJ; Jiang N; Li JY; Tang LL; Xie CM; Huang SM; Ma J; Heng PA; Wee JTS; Chua MLK; Chen H; Sun Y
Radiology; 2019 Jun; 291(3):677-686. PubMed ID: 30912722
[TBL] [Abstract][Full Text] [Related]
5. Semi-supervised model based on implicit neural representation and mutual learning (SIMN) for multi-center nasopharyngeal carcinoma segmentation on MRI.
Han X; Chen Z; Lin G; Lv W; Zheng C; Lu W; Sun Y; Lu L
Comput Biol Med; 2024 Jun; 175():108368. PubMed ID: 38663351
[TBL] [Abstract][Full Text] [Related]
6. The contrast-enhanced MRI can be substituted by unenhanced MRI in identifying and automatically segmenting primary nasopharyngeal carcinoma with the aid of deep learning models: An exploratory study in large-scale population of endemic area.
Deng Y; Li C; Lv X; Xia W; Shen L; Jing B; Li B; Guo X; Sun Y; Xie C; Ke L
Comput Methods Programs Biomed; 2022 Apr; 217():106702. PubMed ID: 35228147
[TBL] [Abstract][Full Text] [Related]
7. Deep learning-based accurate delineation of primary gross tumor volume of nasopharyngeal carcinoma on heterogeneous magnetic resonance imaging: A large-scale and multi-center study.
Luo X; Liao W; He Y; Tang F; Wu M; Shen Y; Huang H; Song T; Li K; Zhang S; Zhang S; Wang G
Radiother Oncol; 2023 Mar; 180():109480. PubMed ID: 36657723
[TBL] [Abstract][Full Text] [Related]
8. A Triple-Classification Radiomics Model for the Differentiation of Primary Chordoma, Giant Cell Tumor, and Metastatic Tumor of Sacrum Based on T2-Weighted and Contrast-Enhanced T1-Weighted MRI.
Yin P; Mao N; Zhao C; Wu J; Chen L; Hong N
J Magn Reson Imaging; 2019 Mar; 49(3):752-759. PubMed ID: 30430686
[TBL] [Abstract][Full Text] [Related]
9. Using the non-distortion IVIM to reduce the need for contrast agents in nasopharyngeal MRI.
Chen R; Ye H; Wu Z; Zhou Y; Lin H; Xu Y; He L; Liang C; Liu Z; Wang G
Magn Reson Imaging; 2023 Dec; 104():115-120. PubMed ID: 37844785
[TBL] [Abstract][Full Text] [Related]
10. Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach.
Lavdas I; Glocker B; Kamnitsas K; Rueckert D; Mair H; Sandhu A; Taylor SA; Aboagye EO; Rockall AG
Med Phys; 2017 Oct; 44(10):5210-5220. PubMed ID: 28756622
[TBL] [Abstract][Full Text] [Related]
11. Predictive value of pretreatment MRI texture analysis in patients with primary nasopharyngeal carcinoma.
Mao J; Fang J; Duan X; Yang Z; Cao M; Zhang F; Lu L; Zhang X; Wu X; Ding Y; Shen J
Eur Radiol; 2019 Aug; 29(8):4105-4113. PubMed ID: 30617473
[TBL] [Abstract][Full Text] [Related]
12. Magnetic Resonance Imaging Features on Deep Learning Algorithm for the Diagnosis of Nasopharyngeal Carcinoma.
Huang R; Zhou Z; Wang X; Cao X
Contrast Media Mol Imaging; 2022; 2022():3790269. PubMed ID: 35677026
[TBL] [Abstract][Full Text] [Related]
13. Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI.
Groendahl AR; Moe YM; Kaushal CK; Huynh BN; Rusten E; Tomic O; Hernes E; Hanekamp B; Undseth C; Guren MG; Malinen E; Futsaether CM
Acta Oncol; 2022 Jan; 61(1):89-96. PubMed ID: 34783610
[TBL] [Abstract][Full Text] [Related]
14. Tumor Segmentation in Contrast-Enhanced Magnetic Resonance Imaging for Nasopharyngeal Carcinoma: Deep Learning with Convolutional Neural Network.
Li Q; Xu Y; Chen Z; Liu D; Feng ST; Law M; Ye Y; Huang B
Biomed Res Int; 2018; 2018():9128527. PubMed ID: 30417017
[TBL] [Abstract][Full Text] [Related]
15. Virtual Contrast-Enhanced Magnetic Resonance Images Synthesis for Patients With Nasopharyngeal Carcinoma Using Multimodality-Guided Synergistic Neural Network.
Li W; Xiao H; Li T; Ren G; Lam S; Teng X; Liu C; Zhang J; Kar-Ho Lee F; Au KH; Ho-Fun Lee V; Chang ATY; Cai J
Int J Radiat Oncol Biol Phys; 2022 Mar; 112(4):1033-1044. PubMed ID: 34774997
[TBL] [Abstract][Full Text] [Related]
16. Fully-Automated Segmentation of Nasopharyngeal Carcinoma on Dual-Sequence MRI Using Convolutional Neural Networks.
Ye Y; Cai Z; Huang B; He Y; Zeng P; Zou G; Deng W; Chen H; Huang B
Front Oncol; 2020; 10():166. PubMed ID: 32154168
[TBL] [Abstract][Full Text] [Related]
17. Convolutional Neural Network Intelligent Segmentation Algorithm-Based Magnetic Resonance Imaging in Diagnosis of Nasopharyngeal Carcinoma Foci.
Wang D; Gong Z; Zhang Y; Wang S
Contrast Media Mol Imaging; 2021; 2021():2033806. PubMed ID: 34456649
[TBL] [Abstract][Full Text] [Related]
18. Discrepant lesion size estimated on T1- and fat-suppressed T2-weighted MRI: diagnostic value for differentiation between inflammatory pseudotumor and carcinoma of the nasopharynx.
Jung HN; Kim HJ; Kim YK; Song M; Kim HY; Park KM; Cha J; Kim ST
Diagn Interv Radiol; 2017; 23(3):199-205. PubMed ID: 28420597
[TBL] [Abstract][Full Text] [Related]
19. Pretreatment MR imaging radiomics signatures for response prediction to induction chemotherapy in patients with nasopharyngeal carcinoma.
Wang G; He L; Yuan C; Huang Y; Liu Z; Liang C
Eur J Radiol; 2018 Jan; 98():100-106. PubMed ID: 29279146
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
