434 related articles for article (PubMed ID: 33194589)
1. Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment.
Hao W; Gong J; Wang S; Zhu H; Zhao B; Peng W
Front Oncol; 2020; 10():531476. PubMed ID: 33194589
[TBL] [Abstract][Full Text] [Related]
2. Magnetic Resonance Imaging Radiomics-Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions.
Hectors SJ; Chen C; Chen J; Wang J; Gordon S; Yu M; Al Hussein Al Awamlh B; Sabuncu MR; Margolis DJA; Hu JC
J Magn Reson Imaging; 2021 Nov; 54(5):1466-1473. PubMed ID: 33970516
[TBL] [Abstract][Full Text] [Related]
3. Radiomics Based on Multimodal MRI for the Differential Diagnosis of Benign and Malignant Breast Lesions.
Zhang Q; Peng Y; Liu W; Bai J; Zheng J; Yang X; Zhou L
J Magn Reson Imaging; 2020 Aug; 52(2):596-607. PubMed ID: 32061014
[TBL] [Abstract][Full Text] [Related]
4. Fully automatic classification of breast lesions on multi-parameter MRI using a radiomics model with minimal number of stable, interpretable features.
Zhang J; Zhan C; Zhang C; Song Y; Yan X; Guo Y; Ai T; Yang G
Radiol Med; 2023 Feb; 128(2):160-170. PubMed ID: 36670236
[TBL] [Abstract][Full Text] [Related]
5. An MRI-Based Radiomics Model for Predicting the Benignity and Malignancy of BI-RADS 4 Breast Lesions.
Zhang R; Wei W; Li R; Li J; Zhou Z; Ma M; Zhao R; Zhao X
Front Oncol; 2021; 11():733260. PubMed ID: 35155178
[TBL] [Abstract][Full Text] [Related]
6. Computer-Aided Diagnosis in Multiparametric Magnetic Resonance Imaging Screening of Women With Extremely Dense Breasts to Reduce False-Positive Diagnoses.
Verburg E; van Gils CH; Bakker MF; Viergever MA; Pijnappel RM; Veldhuis WB; Gilhuijs KGA
Invest Radiol; 2020 Jul; 55(7):438-444. PubMed ID: 32149858
[TBL] [Abstract][Full Text] [Related]
7. Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.
Lee HJ; Nguyen AT; Ki SY; Lee JE; Do LN; Park MH; Lee JS; Kim HJ; Park I; Lim HS
Front Oncol; 2021; 11():744460. PubMed ID: 34926256
[TBL] [Abstract][Full Text] [Related]
8. Value of breast MRI omics features and clinical characteristics in Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions: an analysis of radiomics-based diagnosis.
Cui Q; Sun L; Zhang Y; Zhao Z; Li S; Liu Y; Ge H; Qin D; Zhao Y
Ann Transl Med; 2021 Nov; 9(22):1677. PubMed ID: 34988186
[TBL] [Abstract][Full Text] [Related]
9. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
Wang X; Wan Q; Chen H; Li Y; Li X
Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
[TBL] [Abstract][Full Text] [Related]
10. Texture analysis based on PI-RADS 4/5-scored magnetic resonance images combined with machine learning to distinguish benign lesions from prostate cancer.
Ma L; Zhou Q; Yin H; Ang X; Li Y; Xie G; Li G
Transl Cancer Res; 2022 May; 11(5):1146-1161. PubMed ID: 35706813
[TBL] [Abstract][Full Text] [Related]
11. Radiomics Based on DCE-MRI Improved Diagnostic Performance Compared to BI-RADS Analysis in Identifying Sclerosing Adenosis of the Breast.
Ruan M; Ding Z; Shan Y; Pan S; Shao C; Xu W; Zhen T; Pang P; Shen Q
Front Oncol; 2022; 12():888141. PubMed ID: 35646630
[TBL] [Abstract][Full Text] [Related]
12. Predicting the Grade of Prostate Cancer Based on a Biparametric MRI Radiomics Signature.
Zhang L; Zhe X; Tang M; Zhang J; Ren J; Zhang X; Li L
Contrast Media Mol Imaging; 2021; 2021():7830909. PubMed ID: 35024015
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Radiomics Based on Digital Mammography Helps to Identify Mammographic Masses Suspicious for Cancer.
Wang G; Shi D; Guo Q; Zhang H; Wang S; Ren K
Front Oncol; 2022; 12():843436. PubMed ID: 35433437
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Prediction of Tumor Shrinkage Pattern to Neoadjuvant Chemotherapy Using a Multiparametric MRI-Based Machine Learning Model in Patients With Breast Cancer.
Huang Y; Chen W; Zhang X; He S; Shao N; Shi H; Lin Z; Wu X; Li T; Lin H; Lin Y
Front Bioeng Biotechnol; 2021; 9():662749. PubMed ID: 34295877
[No Abstract] [Full Text] [Related]
17. Differentiation of benign from malignant solid renal lesions with MRI-based radiomics and machine learning.
Massa'a RN; Stoeckl EM; Lubner MG; Smith D; Mao L; Shapiro DD; Abel EJ; Wentland AL
Abdom Radiol (NY); 2022 Aug; 47(8):2896-2904. PubMed ID: 35723716
[TBL] [Abstract][Full Text] [Related]
18. Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI.
Whitney HM; Drukker K; Vieceli M; Van Dusen A; de Oliveira M; Abe H; Giger ML
Med Phys; 2024 Mar; 51(3):1812-1821. PubMed ID: 37602841
[TBL] [Abstract][Full Text] [Related]
19. BI-RADS Reading of Non-Mass Lesions on DCE-MRI and Differential Diagnosis Performed by Radiomics and Deep Learning.
Zhou J; Liu YL; Zhang Y; Chen JH; Combs FJ; Parajuli R; Mehta RS; Liu H; Chen Z; Zhao Y; Pan Z; Wang M; Yu R; Su MY
Front Oncol; 2021; 11():728224. PubMed ID: 34790569
[TBL] [Abstract][Full Text] [Related]
20. A combined radiomics and clinical variables model for prediction of malignancy in T2 hyperintense uterine mesenchymal tumors on MRI.
Wang T; Gong J; Li Q; Chu C; Shen W; Peng W; Gu Y; Li W
Eur Radiol; 2021 Aug; 31(8):6125-6135. PubMed ID: 33486606
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
