The goal of my research is the development and application of machine learning methods to medical imaging, and their translation into clinical practice so that they can help patients on a day-to-day level.
Research projects
Accelerated MR imaging
Machine Learning for MRI data acquisition and image reconstruction
Quantitative imaging biomarkers for disease processes
Increase the global availability of imaging technology in second and third world countries
Current projects
A comprehensive deep learning framework for MRI reconstruction
(Third Party Funds Single)
Term: 1. April 2021 - 31. March 2025 Funding source: National Institutes of Health (NIH)
Sriram, A., Zbontar, J., Murrell, T., Defazio, A., Zitnick, C.L., Yakubova, N.,... Johnson, P. (2020). End-to-End Variational Networks for Accelerated MRI Reconstruction. In Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 64-73). Lima, PER: Springer Science and Business Media Deutschland GmbH.
The goal of my research is the development and application of machine learning methods to medical imaging, and their translation into clinical practice so that they can help patients on a day-to-day level.
Research projects
Current projects
A comprehensive deep learning framework for MRI reconstruction
(Third Party Funds Single)
Funding source: National Institutes of Health (NIH)
Recent publications
2022
2021
2020
Related Research Fields
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