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An MRI-based radiomics model to predict clear cell renal cell carcinoma growth rate classes in patients with von Hippel-Lindau syndrome.
Anari PY, Lay N, Gopal N, Chaurasia A, Samimi S, Harmon S, Firouzabadi FD, Merino MJ, Wakim P, Turkbey E, Jones EC, Ball MW, Turkbey B, Linehan WM, Malayeri AA. Anari PY, et al. Abdom Radiol (NY). 2022 Oct;47(10):3554-3562. doi: 10.1007/s00261-022-03610-5. Epub 2022 Jul 22. Abdom Radiol (NY). 2022. PMID: 35869307 Free PMC article.
Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models.
Reza SMS, Chu WT, Homayounieh F, Blain M, Firouzabadi FD, Anari PY, Lee JH, Worwa G, Finch CL, Kuhn JH, Malayeri A, Crozier I, Wood BJ, Feuerstein IM, Solomon J. Reza SMS, et al. Among authors: anari py. Acad Radiol. 2023 Sep;30(9):2037-2045. doi: 10.1016/j.acra.2023.02.027. Epub 2023 Feb 27. Acad Radiol. 2023. PMID: 36966070 Free PMC article.
Preoperative Renal Parenchyma Volume as a Predictor of Kidney Function Following Nephrectomy of Complex Renal Masses.
Antony MB, Anari PY, Gopal N, Chaurasia A, Firouzabadi FD, Homayounieh F, Kozel Z, Gautam R, Gurram S, Linehan WM, Turkbey EB, Malayeri AA, Ball MW. Antony MB, et al. Among authors: anari py. Eur Urol Open Sci. 2023 Sep 29;57:66-73. doi: 10.1016/j.euros.2023.08.010. eCollection 2023 Nov. Eur Urol Open Sci. 2023. PMID: 38020527 Free PMC article.
Deep learning algorithm (YOLOv7) for automated renal mass detection on contrast-enhanced MRI: a 2D and 2.5D evaluation of results.
Anari PY, Lay N, Zahergivar A, Firouzabadi FD, Chaurasia A, Golagha M, Singh S, Homayounieh F, Obiezu F, Harmon S, Turkbey E, Merino M, Jones EC, Ball MW, Linehan WM, Turkbey B, Malayeri AA. Anari PY, et al. Abdom Radiol (NY). 2024 Apr;49(4):1194-1201. doi: 10.1007/s00261-023-04172-w. Epub 2024 Feb 17. Abdom Radiol (NY). 2024. PMID: 38368481
Automatic segmentation of clear cell renal cell tumors, kidney, and cysts in patients with von Hippel-Lindau syndrome using U-net architecture on magnetic resonance images.
Anari PY, Lay N, Chaurasia A, Gopal N, Samimi S, Harmon S, Gautam R, Ma K, Firouzabadi FD, Turkbey E, Merino M, Jones EC, Ball MW, Linehan WM, Turkbey B, Malayeri AA. Anari PY, et al. ArXiv [Preprint]. 2023 Jan 6:arXiv:2301.02538v1. ArXiv. 2023. PMID: 36789136 Free PMC article. Preprint.