Usman Mahmood
Affiliations: | 2017-2022 | Rochester Institute of Technology, Rochester, NY, United States |
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Sign in to add mentor| Christopher Kanan | grad student | 2017-2022 | Rochester Institute of Technology |
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Publications
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| Samala RK, Drukker K, Shukla-Dave A, et al. (2024) AI and machine learning in medical imaging: key points from development to translation. Bjr Artificial Intelligence. 1: ubae006 |
| Mahmood U, Shukla-Dave A, Chan HP, et al. (2024) Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing. Bjr Artificial Intelligence. 1: ubae003 |
| Paudyal R, Shah AD, Akin O, et al. (2023) Artificial Intelligence in CT and MR Imaging for Oncological Applications. Cancers. 15 |
| Mahmood U, Bates DDB, Erdi YE, et al. (2022) Deep Learning and Domain-Specific Knowledge to Segment the Liver from Synthetic Dual Energy CT Iodine Scans. Diagnostics (Basel, Switzerland). 12 |
| Mahmood U, Apte A, Kanan C, et al. (2021) Quality control of radiomic features using 3D-printed CT phantoms. Journal of Medical Imaging (Bellingham, Wash.). 8: 033505 |
| Oh JH, Apte AP, Katsoulakis E, et al. (2021) Reproducibility of radiomic features using network analysis and its application in Wasserstein -means clustering. Journal of Medical Imaging (Bellingham, Wash.). 8: 031904 |
| Bates DDB, Vintonyak A, Mohabir R, et al. (2020) Use of a portable computed tomography scanner for chest imaging of COVID-19 patients in the urgent care at a tertiary cancer center. Emergency Radiology |
| Mahmood U, Apte AP, Deasy JO, et al. (2017) Investigating the Robustness Neighborhood Gray Tone Difference Matrix and Gray Level Co-occurrence Matrix Radiomic Features on Clinical Computed Tomography Systems Using Anthropomorphic Phantoms: Evidence From a Multivendor Study. Journal of Computer Assisted Tomography |