ArticleNMR in biomedicine2026
Optimal Control-Based Generic Framework for Radiofrequency Pulse Design in MRI.
Article in NMR in biomedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Optimal Control-Based Generic Framework for Radiofrequency Pulse Design in MRI.NMR in biomedicine · 2026Article
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Authors and funding
3 authors.
Funding
Abstract
This work proposes a general framework for the optimal design of radiofrequency pulses in MRI. Based on optimal control theory, it proposes a Python-based numerical implementation using state-of-the-art nonlinear optimization solver (IPOPT). This study proposes three main contributions. It allows the incorporation of hard constraints to the problem and their consistent integration into the optimization process. It proposes to express the pulse as wavelet coefficients which proves to be highly effective in an applicative context. Finally, an innovative approach to minimize the pulse peak amplitude is presented by taking advantage of the efficient constraint management. The proposed framework is made available through a Python package, along with Jupyter Notebooks to reproduce the paper results. It also allows external users to solve their own design problem, benefiting from the generality and flexibility of the proposed implementation. The efficacy of the proposed method is validated in the context of short-
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Registered trials
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