Author

U. Mahmood

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 2

Signature Assays, Organisms & Methods

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Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Approach:statistical model· 1

Frequent Co-Authors

A. Apte· 2 shared J. H. Oh· 2 shared A. Iyer· 1 shared A. S. Dave· 1 shared A. Shukla-Dave· 1 shared A. Tannenbaum· 1 shared C. Kanan· 1 shared D. Bates· 1 shared

Activity by Year

2019-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersBiophysics

A. Apte

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2 papers

Recent·Most cited

Reproducibility test of radiomics using network analysis and Wasserstein K-means algorithm

J. H. Oh, A. Apte, E. Katsoulakis, N. Riaz, V. Hatzoglou, Y. Yu, J. Leeman, U. Mahmood, M. Pouryahya, A. Iyer, A. Shukla-Dave, A. Tannenbaum, N. Lee, J. Deasy

This paper develops a network-based method to identify reproducible radiomic features across different imaging settings and validates it using phantom and external datasets.

bioRxiv · Sep 19, 2019 · PreprintBiophysics

Anatomically Informed 3D Printed CT phantoms: The First Step of a Pipeline To Identify Robust Quantitative Radiomic Features

U. Mahmood, A. Apte, C. Kanan, D. Bates, G. Corrias, L. Mannelli, J. H. Oh, Y. E. Erdi, J. Nguyen, J. O. Deasy, A. S. Dave

This paper demonstrates the feasibility of creating 3D printed CT phantoms from patient data to assess the repeatability and robustness of radiomic features across different scanning parameters.

bioRxiv · Sep 18, 2019 · PreprintBiophysics