140 related articles for article (PubMed ID: 36118892)
21. Diagnostic performance of perilesional radiomics analysis of contrast-enhanced mammography for the differentiation of benign and malignant breast lesions.
Wang S; Sun Y; Li R; Mao N; Li Q; Jiang T; Chen Q; Duan S; Xie H; Gu Y
Eur Radiol; 2022 Jan; 32(1):639-649. PubMed ID: 34189600
[TBL] [Abstract][Full Text] [Related]
22. CT-based radiomics analysis for differentiation between thymoma and thymic carcinoma.
Ohira R; Yanagawa M; Suzuki Y; Hata A; Miyata T; Kikuchi N; Yoshida Y; Yamagata K; Doi S; Ninomiya K; Tomiyama N
J Thorac Dis; 2022 May; 14(5):1342-1352. PubMed ID: 35693628
[TBL] [Abstract][Full Text] [Related]
23. Bi-parametric magnetic resonance imaging based radiomics for the identification of benign and malignant prostate lesions: cross-vendor validation.
Ji X; Zhang J; Shi W; He D; Bao J; Wei X; Huang Y; Liu Y; Chen JC; Gao X; Tang Y; Xia W
Phys Eng Sci Med; 2021 Sep; 44(3):745-754. PubMed ID: 34075559
[TBL] [Abstract][Full Text] [Related]
24. A Novel Nomogram Model Based on Cone-Beam CT Radiomics Analysis Technology for Predicting Radiation Pneumonitis in Esophageal Cancer Patients Undergoing Radiotherapy.
Du F; Tang N; Cui Y; Wang W; Zhang Y; Li Z; Li J
Front Oncol; 2020; 10():596013. PubMed ID: 33392091
[TBL] [Abstract][Full Text] [Related]
25. MRI-based radiomics analysis for differentiating phyllodes tumors of the breast from fibroadenomas.
Tsuchiya M; Masui T; Terauchi K; Yamada T; Katyayama M; Ichikawa S; Noda Y; Goshima S
Eur Radiol; 2022 Jun; 32(6):4090-4100. PubMed ID: 35044510
[TBL] [Abstract][Full Text] [Related]
26. Prediction of Clinical Outcome for High-Intensity Focused Ultrasound Ablation of Uterine Leiomyomas Using Multiparametric MRI Radiomics-Based Machine Leaning Model.
Zheng Y; Chen L; Liu M; Wu J; Yu R; Lv F
Front Oncol; 2021; 11():618604. PubMed ID: 34567999
[TBL] [Abstract][Full Text] [Related]
27. T2-weighted MRI-based radiomics for discriminating between benign and borderline epithelial ovarian tumors: a multicenter study.
Wei M; Zhang Y; Bai G; Ding C; Xu H; Dai Y; Chen S; Wang H
Insights Imaging; 2022 Aug; 13(1):130. PubMed ID: 35943620
[TBL] [Abstract][Full Text] [Related]
28. A multi-organ cancer study of the classification performance using 2D and 3D image features in radiomics analysis.
Xu L; Yang P; Yen EA; Wan Y; Jiang Y; Cao Z; Shen X; Wu Y; Wang J; Luo C; Niu T
Phys Med Biol; 2019 Nov; 64(21):215009. PubMed ID: 31561245
[TBL] [Abstract][Full Text] [Related]
29. Predicting the Level of Tumor-Infiltrating Lymphocytes in Patients With Breast Cancer: Usefulness of Mammographic Radiomics Features.
Yu H; Meng X; Chen H; Liu J; Gao W; Du L; Chen Y; Wang Y; Liu X; Liu B; Fan J; Ma G
Front Oncol; 2021; 11():628577. PubMed ID: 33777776
[TBL] [Abstract][Full Text] [Related]
30. A Clinical-Radiomics Model for Predicting Axillary Pathologic Complete Response in Breast Cancer With Axillary Lymph Node Metastases.
Gan L; Ma M; Liu Y; Liu Q; Xin L; Cheng Y; Xu L; Qin N; Jiang Y; Zhang X; Wang X; Ye J
Front Oncol; 2021; 11():786346. PubMed ID: 34993145
[TBL] [Abstract][Full Text] [Related]
31. An endorectal ultrasound-based radiomics signature for preoperative prediction of lymphovascular invasion of rectal cancer.
Wu YQ; Gao RZ; Lin P; Wen R; Li HY; Mou MY; Chen FH; Huang F; Zhou WJ; Yang H; He Y; Wu J
BMC Med Imaging; 2022 May; 22(1):84. PubMed ID: 35538520
[TBL] [Abstract][Full Text] [Related]
32. Radiomics in predicting tumor molecular marker P63 for non-small cell lung cancer.
Gu Q; Feng Z; Hu X; Ma M; Mustafa Jumbe M; Yan H; Liu P; Rong P
Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2019 Sep; 44(9):1055-1062. PubMed ID: 31645497
[TBL] [Abstract][Full Text] [Related]
33. Comparison of the application of B-mode and strain elastography ultrasound in the estimation of lymph node metastasis of papillary thyroid carcinoma based on a radiomics approach.
Liu T; Ge X; Yu J; Guo Y; Wang Y; Wang W; Cui L
Int J Comput Assist Radiol Surg; 2018 Oct; 13(10):1617-1627. PubMed ID: 29931410
[TBL] [Abstract][Full Text] [Related]
34. Prediction of Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma: A Radiomics Method Based on Preoperative Ultrasound Images.
Liu T; Zhou S; Yu J; Guo Y; Wang Y; Zhou J; Chang C
Technol Cancer Res Treat; 2019 Jan; 18():1533033819831713. PubMed ID: 30890092
[TBL] [Abstract][Full Text] [Related]
35. Potential feature exploration and model development based on 18F-FDG PET/CT images for differentiating benign and malignant lung lesions.
Zhang R; Zhu L; Cai Z; Jiang W; Li J; Yang C; Yu C; Jiang B; Wang W; Xu W; Chai X; Zhang X; Tang Y
Eur J Radiol; 2019 Dec; 121():108735. PubMed ID: 31733432
[TBL] [Abstract][Full Text] [Related]
36. Incorporating the clinical and radiomics features of contrast-enhanced mammography to classify breast lesions: a retrospective study.
Wang S; Sun Y; Mao N; Duan S; Li Q; Li R; Jiang T; Wang Z; Xie H; Gu Y
Quant Imaging Med Surg; 2021 Oct; 11(10):4418-4430. PubMed ID: 34603996
[TBL] [Abstract][Full Text] [Related]
37. Apparent Diffusion Coefficient Map-Based Radiomics Features for Differential Diagnosis of Pleomorphic Adenomas and Warthin Tumors From Malignant Tumors.
Wen B; Zhang Z; Zhu J; Liu L; Li Y; Huang H; Zhang Y; Cheng J
Front Oncol; 2022; 12():830496. PubMed ID: 35747827
[TBL] [Abstract][Full Text] [Related]
38. An investigation of machine learning methods in delta-radiomics feature analysis.
Chang Y; Lafata K; Sun W; Wang C; Chang Z; Kirkpatrick JP; Yin FF
PLoS One; 2019; 14(12):e0226348. PubMed ID: 31834910
[TBL] [Abstract][Full Text] [Related]
39. A radiomics method based on MR FS-T2WI sequence for diagnosing of autosomal dominant polycystic kidney disease progression.
Cong L; Hua QQ; Huang ZQ; Ma QL; Wang XM; Huang CC; Xu JX; Ma T
Eur Rev Med Pharmacol Sci; 2021 Sep; 25(18):5769-5780. PubMed ID: 34604968
[TBL] [Abstract][Full Text] [Related]
40. A CT-Based Radiomics Nomogram to Predict Complete Ablation of Pulmonary Malignancy: A Multicenter Study.
Zhang G; Yang H; Zhu X; Luo J; Zheng J; Xu Y; Zheng Y; Wei Y; Mei Z; Shao G
Front Oncol; 2022; 12():841678. PubMed ID: 35223526
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
