| Deployed deep learning kidney segmentation for polycystic kidney disease MRI A Goel, G Shih, S Riyahi, S Jeph, H Dev, R Hu, D Romano, K Teichman, ... Radiology: Artificial Intelligence 4 (2), e210205, 2022 | 35 | 2022 |
| Deep learning automation of kidney, liver, and spleen segmentation for organ volume measurements in autosomal dominant polycystic kidney disease A Sharbatdaran, D Romano, K Teichman, H Dev, SI Raza, A Goel, ... Tomography 8 (4), 1804-1819, 2022 | 17 | 2022 |
| Test retest reproducibility of organ volume measurements in ADPKD using 3D multimodality deep learning X He, Z Hu, H Dev, DJ Romano, A Sharbatdaran, SI Raza, SJ Wang, ... Academic Radiology 31 (3), 889-899, 2024 | 7 | 2024 |
| Effect of averaging measurements from multiple MRI pulse sequences on kidney volume reproducibility in autosomal dominant polycystic kidney disease H Dev, C Zhu, A Sharbatdaran, SI Raza, SJ Wang, DJ Romano, A Goel, ... Journal of Magnetic Resonance Imaging 58 (4), 1153-1160, 2023 | 7 | 2023 |
| Tracking of endothelial cell migration and stiffness measurements reveal the role of cytoskeletal dynamics DJ Romano, JM Gomez-Salinero, Z Šunić, A Checco, SY Rabbany International journal of molecular sciences 23 (1), 568, 2022 | 6 | 2022 |
| Deep learning-based liver cyst segmentation in MRI for autosomal dominant polycystic kidney disease M Chookhachizadeh Moghadam, M Aspal, X He, DJ Romano, ... Radiology Advances 1 (2), 2024 | 1 | 2024 |
| Maximum spherical mean value filtering for whole‐brain QSM AG Roberts, DJ Romano, M Şişman, AV Dimov, TD Nguyen, ... Magnetic Resonance in Medicine 91 (4), 1586-1597, 2024 | 1 | 2024 |
| IRIS—Intelligent Rapid Interactive Segmentation for Measuring Liver Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease C Li, D Romano, SJ Wang, H Zhang, MR Prince, Y Wang Tomography 8 (1), 447-456, 2022 | 1 | 2022 |
| A Primer for Utilizing Deep Learning and Abdominal MRI Imaging Features to Monitor Autosomal Dominant Polycystic Kidney Disease Progression C Zhu, X He, JD Blumenfeld, Z Hu, H Dev, U Sattar, V Bazojoo, ... Biomedicines 12 (5), 1133, 2024 | | 2024 |
| Microstructure-Informed Myelin Mapping (MIMM) from Gradient Echo MRI using Stochastic Matching Pursuit M Şişman, TD Nguyen, AG Roberts, DJ Romano, AV Dimov, ... medRxiv, 2023.09. 22.23295993, 2023 | | 2023 |
| Fluid mechanics based automated quantitative transport mapping (QTM) without arterial input for quantifying 11C-PE2I PET in Parkinson’s disease Q Zhang, D Romano, P Spincemaille, G Chiang, Y Wang Journal of Nuclear Medicine 64 (supplement 1), P1214-P1214, 2023 | | 2023 |
| Maximum Spherical Mean Value (mSMV) Filtering for Whole Brain Quantitative Susceptibility Mapping AG Roberts, DJ Romano, M Şişman, AV Dimov, P Spincemaille, ... arXiv preprint arXiv:2304.11476, 2023 | | 2023 |
| Estimation of 11 C-PE2I PET based cerebral perfusion in Parkinson’s disease patients using quantitative transport mapping network (QTMnet) Proc Q Zhang, D Romano, KMC Gillen, C Skudin, S Alexander, T Nguyen, ... Intl. Soc. Mag. Reson. Med 31, 2023, 2023 | | 2023 |
| Mapping Myelin Volume Fraction using Multiple Echo Gradient Echo and Dictionary Matching M Şişman, DJ Romano, AV Dimov, I Kovanlikaya, P Spincemaille, ... | | 2023 |
| Radiomic Prediction of Parkinson’s Disease Deep Brain Stimulation Surgery Outcomes using Quantitative Susceptibility Mapping and Label Noise Compensation AG Roberts, J Zhang, C Tozlu, S Akkus, D Romano, X Wu, J Li, H Kim, ... | | |
| Improving Kidney Volume Measurement Reproducibility in ADPKD by Averaging Measurements on Multiple Sequences H Dev, C Zhu, A Sharbatdaran, SI Raza, S Wang, DJ Romano, A Goel, ... | | |
| Building a Liver Perfusion Phantom for Vessel Size Imaging DJ Romano, M Şişman, Q Zhang, T Nguyen, P Spincemaille, M Prince, ... | | |
| Comparing L1 and L2 Regularizations for Quantitative Transport Mapping of Tumor: an Image Quality Analysis D Romano, Q Zhang, I Kovanlikaya, P Spincemaille, Y Wang | | |
| Pathological Validation of Multiple Sclerosis Lesion Rims on Phase and Quantitative Susceptibility Mapping (QSM) images KM Gillen, TD Nguyen, A Dimov, E Demmon, I Kovanlikaya, F Bagnato, ... | | |
| Quantitative transport mapping (QTM) of the brain with simulated microvasculature model R Hu, Q Zhang, DJ Romano, Y Wang | | |
Hreedi DevWeill Cornell Medicine在 med.cornell.edu 的电子邮件经过验证
