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Amir A. Amini
Researcher at University of Louisville
Publications - 151
Citations - 5238
Amir A. Amini is an academic researcher from University of Louisville. The author has contributed to research in topics: Optical flow & Imaging phantom. The author has an hindex of 27, co-authored 146 publications receiving 4916 citations. Previous affiliations of Amir A. Amini include University of Washington & Veterans Health Administration.
Papers
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Using dynamic programming for solving variational problems in vision: applications involving deformable models for contours and surfaces.
TL;DR: In this paper, the authors apply dynamic programming to the energy-minimizing active contours optimization problem, which is set up as a discrete multistage decision process and is solved by a time-delayed discrete dynamic programming algorithm.
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Using dynamic programming for solving variational problems in vision
TL;DR: The optimization problem is set up as a discrete multistage decision process and is solved by a time-delayed discrete dynamic programming algorithm, and a parallel procedure for decreasing computational costs is discussed.
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Using Dynamic Programming For Minimizing The Energy Of Active Contours In The Presence Of Hard Constraints
TL;DR: The optimization problem is set up as a discrete multi-stage decision process and is solved by a “time-delayed” discrete dynamic programming algorithm, which leads to a stable behavior for the active contours over iterations, in addition to allowing for hard constraints to be enforced on the behavior of the solution.
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AI in Medical Imaging Informatics: Current Challenges and Future Directions
Andreas S. Panayides,Amir A. Amini,Nenad Filipovic,Ashish Sharma,Sotirios A. Tsaftaris,Alistair A. Young,David J. Foran,Nhan Do,Spyretta Golemati,Tahsin Kurc,Kun Huang,Konstantina S. Nikita,Ben P. Veasey,Michalis Zervakis,Joel H. Saltz,Constantinos S. Pattichis +15 more
TL;DR: Integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications.
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Coupled B-snake grids and constrained thin-plate splines for analysis of 2-D tissue deformations from tagged MRI
TL;DR: The implementation proposed in this paper improves on the authors' previous variational-based implementation and generalizes warp methods to include biologically relevant contiguous open curves, in addition to standard landmark points.