32 results on '"Ruan, Guangying"'
Search Results
2. Optimal cut‐off value for identifying objective response in patients with nasopharyngeal carcinoma after induction chemotherapy
3. Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma
4. Value of radiological depth of invasion in non-pT4 Oral tongue squamous cell carcinoma: implication for preoperative MR T-staging
5. TdDS-UNet: top-down deeply supervised U-Net for the delineation of 3D colorectal cancer
6. A Rulefit-based prognostic analysis using structured MRI report to select potential beneficiaries from induction chemotherapy in advanced nasopharyngeal carcinoma: A dual-centre study
7. Matted Lymph Nodes on MRI in Nasopharyngeal Carcinoma: Prognostic Factor and Potential Indication for Induction Chemotherapy Benefits
8. P1172: ARTIFICIAL INTELLIGENCE FOR PROGNOSIS PREDICTION OF NATURAL KILLER/T-CELL LYMPHOMA BASED ON MAGNETIC RESONANCE IMAGING
9. Multiscale feature fusion network for 3D head MRI image registration
10. Synergistic Association of Hepatitis B Surface Antigen and Plasma Epstein-Barr Virus DNA Load on Distant Metastasis in Patients With Nasopharyngeal Carcinoma
11. Prognostic potential of a voxelwise invasion risk map of nasopharyngeal carcinoma based on a coordinate system of the nasopharynx
12. BSMM-Net: Multi-modal neural network based on bilateral symmetry for nasopharyngeal carcinoma segmentation
13. Carotid space involvement is a prognostic factor and marker for induction chemotherapy in patients with nasopharyngeal carcinoma
14. MRI ‐Based Metastatic Nodal Number and Associated Nomogram Improve Stratification of Nasopharyngeal Carcinoma Patients: Potential Indications for Individual Induction Chemotherapy
15. RuleFit-Based Nomogram Using Inflammatory Indicators for Predicting Survival in Nasopharyngeal Carcinoma, a Bi-Center Study
16. Survival impact of additional induction chemotherapy in nasopharyngeal carcinoma with chronic hepatitis B infection: a retrospective, bi-center study
17. Value of skull base invasion subclassification in nasopharyngeal carcinoma: implication for prognostic stratification and use of induction chemotherapy
18. SeqSeg: A sequential method to achieve nasopharyngeal carcinoma segmentation free from background dominance
19. Prognostic value of quantitative cervical nodal necrosis burden on MRI in nasopharyngeal carcinoma and its role as a stratification marker for induction chemotherapy
20. Deep learning–based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study
21. Automatic location scheme of anatomical landmarks in 3D head MRI based on the scale attention hourglass network
22. Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma
23. MRI of nasopharyngeal carcinoma: parapharyngeal subspace involvement has prognostic value and influences T-staging in the IMRT era
24. Differences in Radiomics Signatures Between Patients with Early and Advanced T‐Stage Nasopharyngeal Carcinoma Facilitate Prognostication
25. Excessive vitamin B6 during treatment is related to poor prognosis of patients with nasopharyngeal carcinoma: A U-shaped distribution suggests low dose supplement
26. Segmentation and Registration of the Liver in Dynamic Contrast-Enhanced Computed Tomography Images
27. Grading Soft Tissue Involvement in Nasopharyngeal Carcinoma Using Network and Survival Analyses: A Two‐Center Retrospective Study
28. Time-to-Event Supervised Genetic Algorithm Enables Induction Chemotherapy Decision Making for Nasopharyngeal Carcinoma
29. Prognostic Value of Nodal Matting on MRI in Nasopharyngeal Carcinoma Patients
30. Anatomical Point-of-Interest Detection in Head MRI Using Multipoint Feature Descriptor
31. Percutaneous microwave ablation versus surgical resection for ovarian cancer liver metastasis
32. Differentiation Between Benign and Nonbenign Meningiomas by Using Texture Analysis From Multiparametric MRI
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