| A dataset and a technique for generalized nuclear segmentation for computational pathology N Kumar, R Verma, S Sharma, S Bhargava, A Vahadane, A Sethi IEEE transactions on medical imaging 36 (7), 1550-1560, 2017 | 890 | 2017 |
| A Multi-organ Nucleus Segmentation Challenge N Kumar, R Verma, D Anand, Y Zhou, OF Onder, E Tsougenis, H Chen, ... IEEE transactions on medical imaging, 2019 | 393 | 2019 |
| Federated learning enables big data for rare cancer boundary detection S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ... Nature communications 13 (1), 7346, 2022 | 152 | 2022 |
| MoNuSAC2020: A multi-organ nuclei segmentation and classification challenge R Verma, N Kumar, A Patil, NC Kurian, S Rane, S Graham, QD Vu, ... IEEE Transactions on Medical Imaging 40 (12), 3413-3423, 2021 | 124 | 2021 |
| Radiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma N Beig, K Bera, P Prasanna, J Antunes, R Correa, S Singh, ... Clinical Cancer Research 26 (8), 1866-1876, 2020 | 87 | 2020 |
| Convolutional neural networks for wavelet domain super resolution N Kumar, R Verma, A Sethi Pattern Recognition Letters 90, 65-71, 2017 | 59 | 2017 |
| Convolutional neural networks for prostate cancer recurrence prediction N Kumar, R Verma, A Arora, A Kumar, S Gupta, A Sethi, PH Gann Medical Imaging 2017: Digital Pathology 10140, 101400H, 2017 | 58 | 2017 |
| MRQy—An open‐source tool for quality control of MR imaging data AR Sadri, A Janowczyk, R Zhou, R Verma, N Beig, J Antunes, ... Medical Physics 47 (12), 6029-6038, 2020 | 47 | 2020 |
| Multi-organ nuclei segmentation and classification challenge 2020 R Verma, N Kumar, A Patil, NC Kurian, S Rane, A Sethi IEEE transactions on medical imaging 39 (1380-1391), 8, 2020 | 37 | 2020 |
| Reproducibility analysis of multi‐institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset S Pati, R Verma, H Akbari, M Bilello, VB Hill, C Sako, R Correa, N Beig, ... Medical Physics 47 (12), 6039-6052, 2020 | 30 | 2020 |
| Tumor habitat–derived radiomic features at pretreatment MRI that are prognostic for progression-free survival in glioblastoma are associated with key morphologic attributes at … R Verma, R Correa, VB Hill, V Statsevych, K Bera, N Beig, A Mahammedi, ... Radiology: Artificial Intelligence 2 (6), e190168, 2020 | 29 | 2020 |
| Detecting multiple sub-types of breast cancer in a single patient R Verma, N Kumar, A Sethi, PH Gann 2016 IEEE International Conference on Image Processing (ICIP), 2648-2652, 2016 | 16 | 2016 |
| The Pursuit of Generalizability to Enable Clinical Translation of Radiomics P Tiwari, R Verma Radiology: Artificial Intelligence 3 (1), e200227, 2020 | 10 | 2020 |
| Computer extracted features of nuclear morphology in hematoxylin and eosin images distinguish Stage II and IV colon tumors N Kumar, R Verma, C Chen, C Lu, P Fu, J Willis, A Madabhushi The Journal of Pathology, 2022 | 9 | 2022 |
| Stable and Discriminatory Radiomic Features from the Tumor and Its Habitat Associated with Progression-Free Survival in Glioblastoma: A Multi-Institutional Study R Verma, VB Hill, V Statsevych, K Bera, R Correa, P Leo, M Ahluwalia, ... American Journal of Neuroradiology 43 (8), 1115-1123, 2022 | 7 | 2022 |
| Combining deep and hand-crafted MRI features for identifying sex-specific differences in autism spectrum disorder versus controls Y Hiremath, M Ismail, R Verma, J Antunes, P Tiwari Medical Imaging 2020: Computer-Aided Diagnosis 11314, 445-451, 2020 | 5 | 2020 |
| Author’s Reply to “MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge” R Verma, N Kumar, A Patil, NC Kurian, S Rane, A Sethi IEEE Transactions on Medical Imaging 41 (4), 1000-1003, 2022 | 4 | 2022 |
| Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction S Qi, N Kumar, R Verma, JY Xu, G Shen-Tu, R Greiner IEEE Transactions on Biomedical Engineering, 2023 | 3 | 2023 |
| Author Correction: Federated learning enables big data for rare cancer boundary detection S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ... Nature communications 14 (1), 436, 2023 | 3 | 2023 |
| Novel MRI deformation-heterogeneity radiomic features are associated with molecular subgroups and overall survival in pediatric medulloblastoma: Preliminary findings from a … S Iyer, M Ismail, B Tamrazi, R Salloum, P de Blank, A Margol, R Correa, ... Frontiers in Oncology 12, 915143, 2022 | 3 | 2022 |
Pallavi TiwariAssociate Professor, Department of Radiology & Biomedical Engineering, UW-Madison在 wisc.edu 的电子邮件经过验证
