102 related articles for article (PubMed ID: 38733369)
1. Reproducible Radiomics Features from Multi-MRI-Scanner Test-Retest-Study: Influence on Performance and Generalizability of Models.
Wennmann M; Rotkopf LT; Bauer F; Hielscher T; Kächele J; Mai EK; Weinhold N; Raab MS; Goldschmidt H; Weber TF; Schlemmer HP; Delorme S; Maier-Hein K; Neher P
J Magn Reson Imaging; 2024 May; ():. PubMed ID: 38733369
[TBL] [Abstract][Full Text] [Related]
2. In Vivo Repeatability and Multiscanner Reproducibility of MRI Radiomics Features in Patients With Monoclonal Plasma Cell Disorders: A Prospective Bi-institutional Study.
Wennmann M; Bauer F; Klein A; Chmelik J; Grözinger M; Rotkopf LT; Neher P; Gnirs R; Kurz FT; Nonnenmacher T; Sauer S; Weinhold N; Goldschmidt H; Kleesiek J; Bonekamp D; Weber TF; Delorme S; Maier-Hein K; Schlemmer HP; Götz M
Invest Radiol; 2023 Apr; 58(4):253-264. PubMed ID: 36165988
[TBL] [Abstract][Full Text] [Related]
3. Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.
Cheong EN; Park JE; Park SY; Jung SC; Kim HS
Eur Radiol; 2024 Mar; 34(3):2008-2023. PubMed ID: 37665391
[TBL] [Abstract][Full Text] [Related]
4. Prediction of Bone Marrow Biopsy Results From MRI in Multiple Myeloma Patients Using Deep Learning and Radiomics.
Wennmann M; Ming W; Bauer F; Chmelik J; Klein A; Uhlenbrock C; Grözinger M; Kahl KC; Nonnenmacher T; Debic M; Hielscher T; Thierjung H; Rotkopf LT; Stanczyk N; Sauer S; Jauch A; Götz M; Kurz FT; Schlamp K; Horger M; Afat S; Besemer B; Hoffmann M; Hoffend J; Kraemer D; Graeven U; Ringelstein A; Bonekamp D; Kleesiek J; Floca RO; Hillengass J; Mai EK; Weinhold N; Weber TF; Goldschmidt H; Schlemmer HP; Maier-Hein K; Delorme S; Neher P
Invest Radiol; 2023 Oct; 58(10):754-765. PubMed ID: 37222527
[TBL] [Abstract][Full Text] [Related]
5. Peritumoral and Intratumoral Texture Features Based on Multiparametric MRI and Multiple Machine Learning Methods to Preoperatively Evaluate the Pathological Outcomes of Pancreatic Cancer.
Xie N; Fan X; Chen D; Chen J; Yu H; He M; Liu H; Yin X; Li B; Wang H
J Magn Reson Imaging; 2023 Aug; 58(2):379-391. PubMed ID: 36426965
[TBL] [Abstract][Full Text] [Related]
6. Preoperative MRI-Based Radiomic Machine-Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft-Tissue Lesions: A Two-Center Study.
Wang H; Zhang J; Bao S; Liu J; Hou F; Huang Y; Chen H; Duan S; Hao D; Liu J
J Magn Reson Imaging; 2020 Sep; 52(3):873-882. PubMed ID: 32112598
[TBL] [Abstract][Full Text] [Related]
7. MRI-Based Machine Learning Radiomics for Preoperative Assessment of Human Epidermal Growth Factor Receptor 2 Status in Urothelial Bladder Carcinoma.
Yu R; Cai L; Gong Y; Sun X; Li K; Cao Q; Yang X; Lu Q
J Magn Reson Imaging; 2024 Mar; ():. PubMed ID: 38456745
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Preoperative Evaluation of Gd-EOB-DTPA-Enhanced MRI Radiomics-Based Nomogram in Small Solitary Hepatocellular Carcinoma (≤3 cm) With Microvascular Invasion: A Two-Center Study.
Tian Y; Hua H; Peng Q; Zhang Z; Wang X; Han J; Ma W; Chen J
J Magn Reson Imaging; 2022 Nov; 56(5):1459-1472. PubMed ID: 35298849
[TBL] [Abstract][Full Text] [Related]
10. A Multi-Center, Multi-Vendor Study to Evaluate the Generalizability of a Radiomics Model for Classifying Prostate cancer: High Grade vs. Low Grade.
Castillo T JM; Starmans MPA; Arif M; Niessen WJ; Klein S; Bangma CH; Schoots IG; Veenland JF
Diagnostics (Basel); 2021 Feb; 11(2):. PubMed ID: 33671533
[TBL] [Abstract][Full Text] [Related]
11. Impact of signal intensity normalization of MRI on the generalizability of radiomic-based prediction of molecular glioma subtypes.
Foltyn-Dumitru M; Schell M; Rastogi A; Sahm F; Kessler T; Wick W; Bendszus M; Brugnara G; Vollmuth P
Eur Radiol; 2024 Apr; 34(4):2782-2790. PubMed ID: 37672053
[TBL] [Abstract][Full Text] [Related]
12. Multiparametric Magnetic Resonance Imaging-Based Peritumoral Radiomics for Preoperative Prediction of the Presence of Extracapsular Extension With Prostate Cancer.
Bai H; Xia W; Ji X; He D; Zhao X; Bao J; Zhou J; Wei X; Huang Y; Li Q; Gao X
J Magn Reson Imaging; 2021 Oct; 54(4):1222-1230. PubMed ID: 33970517
[TBL] [Abstract][Full Text] [Related]
13. Machine learning-based radiomics model to predict benign and malignant PI-RADS v2.1 category 3 lesions: a retrospective multi-center study.
Jin P; Shen J; Yang L; Zhang J; Shen A; Bao J; Wang X
BMC Med Imaging; 2023 Mar; 23(1):47. PubMed ID: 36991347
[TBL] [Abstract][Full Text] [Related]
14. Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation.
Liu Y; Zhang Y; Cheng R; Liu S; Qu F; Yin X; Wang Q; Xiao B; Ye Z
J Magn Reson Imaging; 2019 Jan; 49(1):280-290. PubMed ID: 29761595
[TBL] [Abstract][Full Text] [Related]
15. Natural Changes in Radiological and Radiomics Features on MRIs of Soft-Tissue Sarcomas Naïve of Treatment: Correlations With Histology and Patients' Outcomes.
Fadli D; Kind M; Michot A; Le Loarer F; Crombé A
J Magn Reson Imaging; 2022 Jul; 56(1):77-96. PubMed ID: 34939705
[TBL] [Abstract][Full Text] [Related]
16. Association of Pathological Features and Multiparametric MRI-Based Radiomics With TP53-Mutated Prostate Cancer.
Chen R; Zhou B; Liu W; Gan H; Liu X; Zhou L
J Magn Reson Imaging; 2023 Dec; ():. PubMed ID: 38153859
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Multiparametric MRI-Based Interpretable Radiomics Machine Learning Model Differentiates Medulloblastoma and Ependymoma in Children: A Two-Center Study.
Yimit Y; Yasin P; Tuersun A; Wang J; Wang X; Huang C; Abudoubari S; Chen X; Ibrahim I; Nijiati P; Wang Y; Zou X; Nijiati M
Acad Radiol; 2024 Mar; ():. PubMed ID: 38508934
[TBL] [Abstract][Full Text] [Related]
19. Prediction of High-Risk Cytogenetic Status in Multiple Myeloma Based on Magnetic Resonance Imaging: Utility of Radiomics and Comparison of Machine Learning Methods.
Liu J; Zeng P; Guo W; Wang C; Geng Y; Lang N; Yuan H
J Magn Reson Imaging; 2021 Oct; 54(4):1303-1311. PubMed ID: 33979466
[TBL] [Abstract][Full Text] [Related]
20. Radiomics and Machine Learning With Multiparametric Preoperative MRI May Accurately Predict the Histopathological Grades of Soft Tissue Sarcomas.
Wang H; Chen H; Duan S; Hao D; Liu J
J Magn Reson Imaging; 2020 Mar; 51(3):791-797. PubMed ID: 31486565
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]