| Quantitative analysis of vascular properties derived from ultrafast DCE‐MRI to discriminate malignant and benign breast tumors C Wu, F Pineda, DA Hormuth, GS Karczmar, TE Yankeelov Magnetic resonance in medicine 81 (3), 2147-2160, 2019 | 67 | 2019 |
| Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting AG Sorace, C Wu, SL Barnes, AM Jarrett, S Avery, D Patt, B Goodgame, ... Journal of Magnetic Resonance Imaging 48 (3), 695-707, 2018 | 57 | 2018 |
| Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology C Wu, G Lorenzo, DA Hormuth, EABF Lima, KP Slavkova, JC DiCarlo, ... Biophysics Reviews 3 (2), 021304, 2022 | 54 | 2022 |
| Evaluating patient-specific neoadjuvant regimens for breast cancer via a mathematical model constrained by quantitative magnetic resonance imaging data AM Jarrett, DA Hormuth II, C Wu, AS Kazerouni, DA Ekrut, J Virostko, ... Neoplasia 22 (12), 820-830, 2020 | 48 | 2020 |
| Biologically-Based Mathematical Modeling of Tumor Vasculature and Angiogenesis via Time-Resolved Imaging Data DA Hormuth, CM Phillips, C Wu, EABF Lima, G Lorenzo, PK Jha, ... Cancers 13 (12), 3008, 2021 | 44 | 2021 |
| MRI-based digital models forecast patient-specific treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer C Wu, AM Jarrett, Z Zhou, N Elshafeey, BE Adrada, RP Candelaria, ... Cancer Research 82 (18), 3394-3404, 2022 | 40 | 2022 |
| Evaluating multisite rCBV consistency from DSC-MRI imaging protocols and postprocessing software across the NCI Quantitative Imaging Network sites using a digital reference … LC Bell, N Semmineh, H An, C Eldeniz, R Wahl, KM Schmainda, MA Prah, ... Tomography 5 (1), 110-117, 2019 | 35 | 2019 |
| Patient-specific characterization of breast cancer hemodynamics using image-guided computational fluid dynamics C Wu, DA Hormuth, TA Oliver, F Pineda, G Lorenzo, GS Karczmar, ... IEEE transactions on medical imaging 39 (9), 2760-2771, 2020 | 31 | 2020 |
| Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting AM Jarrett, AS Kazerouni, C Wu, J Virostko, AG Sorace, JC DiCarlo, ... Nature protocols 16 (11), 5309-5338, 2021 | 30 | 2021 |
| Math, magnets, and medicine: enabling personalized oncology DA Hormuth, AM Jarrett, G Lorenzo, EABF Lima, C Wu, C Chung, D Patt, ... Expert Review of Precision Medicine and Drug Development 6 (2), 79-81, 2021 | 23 | 2021 |
| Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas A Chaudhuri, G Pash, DA Hormuth, G Lorenzo, M Kapteyn, C Wu, ... Frontiers in Artificial Intelligence 6, 1222612, 2023 | 20 | 2023 |
| A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue M Fritz, T Köppl, JT Oden, A Wagner, B Wohlmuth, C Wu International Journal for Numerical Methods in Biomedical Engineering 38 (7 …, 2022 | 17 | 2022 |
| Towards patient-specific optimization of neoadjuvant treatment protocols for breast cancer based on image-guided fluid dynamics C Wu, DA Hormuth, G Lorenzo, AM Jarrett, F Pineda, FM Howard, ... IEEE Transactions on Biomedical Engineering 69 (11), 3334-3344, 2022 | 16 | 2022 |
| Patient specific, imaging-informed modeling of rhenium-186 nanoliposome delivery via convection-enhanced delivery in glioblastoma multiforme RT Woodall, DA Hormuth II, C Wu, MRA Abdelmalik, WT Phillips, A Bao, ... Biomedical Physics & Engineering Express 7 (4), 045012, 2021 | 14 | 2021 |
| Evaluating the use of rCBV as a tumor grade and treatment response classifier across NCI Quantitative Imaging Network sites: part II of the DSC-MRI digital reference object … LC Bell, N Semmineh, H An, C Eldeniz, R Wahl, KM Schmainda, MA Prah, ... Tomography 6 (2), 203-208, 2020 | 14 | 2020 |
| Magnetization transfer MRI of breast cancer in the community setting: reproducibility and preliminary results in neoadjuvant therapy J Virostko, AG Sorace, C Wu, D Ekrut, AM Jarrett, RM Upadhyaya, S Avery, ... Tomography 5 (1), 44-52, 2019 | 11 | 2019 |
| Designing clinical trials for patients who are not average TE Yankeelov, DA Hormuth, EABF Lima, G Lorenzo, C Wu, LC Okereke, ... Iscience 27 (1), 2024 | 9 | 2024 |
| An untrained deep learning method for reconstructing dynamic MR images from accelerated model‐based data KP Slavkova, JC DiCarlo, V Wadhwa, S Kumar, C Wu, J Virostko, ... Magnetic Resonance in Medicine 89 (4), 1617-1633, 2023 | 9 | 2023 |
| Abstract P2-16-17: Optimizing neoadjuvant regimens for individual breast cancer patients generated by a mathematical model utilizing quantitative magnetic resonance imaging … AM Jarrett, DA Hormuth, C Wu, J Virostko, AG Sorace, JC DiCarlo, D Patt, ... Cancer Research 80 (4_Supplement), P2-16-17-P2-16-17, 2020 | 6 | 2020 |
| An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom C Wu, DA Hormuth II, T Easley, V Eijkhout, F Pineda, GS Karczmar, ... Medical image analysis 73, 102186, 2021 | 5 | 2021 |
Thomas YankeelovDirector, Center for Computational Oncology, The University of Texas at AustinVerified email at utexas.edu
