Ragini Verma
Affiliations: | Bioengineering | University of Pennsylvania, Philadelphia, PA, United States |
Area:
Radiology, Biomedical Engineering, PathologyGoogle:
"Ragini Verma"
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Publications
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| Parker D, Ould Ismail AA, Wolf R, et al. (2020) Freewater estimatoR using iNtErpolated iniTialization (FERNET): Characterizing peritumoral edema using clinically feasible diffusion MRI data. Plos One. 15: e0233645 |
| Henderson F, Abdullah KG, Verma R, et al. (2020) Tractography and the connectome in neurosurgical treatment of gliomas: the premise, the progress, and the potential. Neurosurgical Focus. 48: E6 |
| Tunç B, Yankowitz LD, Parker D, et al. (2019) Deviation from normative brain development is associated with symptom severity in autism spectrum disorder. Molecular Autism. 10: 46 |
| Shinohara RT, Shou H, Carone M, et al. (2019) Distance-Based Analysis of Variance for Brain Connectivity. Biometrics |
| Nath V, Schilling KG, Parvathaneni P, et al. (2019) Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challenge. Journal of Magnetic Resonance Imaging : Jmri |
| Osmanlıoğlu Y, Tunç B, Parker D, et al. (2019) System-level matching of structural and functional connectomes in the human brain. Neuroimage |
| Schilling KG, Nath V, Hansen C, et al. (2018) Limits to anatomical accuracy of diffusion tractography using modern approaches. Neuroimage |
| Baum GL, Roalf DR, Cook PA, et al. (2018) The impact of in-scanner head motion on structural connectivity derived from diffusion MRI. Neuroimage |
| Davatzikos C, Rathore S, Bakas S, et al. (2018) Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome. Journal of Medical Imaging (Bellingham, Wash.). 5: 011018 |
| Zhang F, Savadjiev P, Cai W, et al. (2017) Whole brain white matter connectivity analysis using machine learning: An application to autism. Neuroimage |