[IPOL announce] new article: Electron Paramagnetic Resonance Image Reconstruction with Total Variation Regularization
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Tue Mar 21 19:16:38 CET 2023
A new article is available in IPOL: https://www.ipol.im/pub/art/2023/414/
Rémy Abergel, Mehdi Boussâa, Sylvain Durand, and Yves-Michel Frapart,
Electron Paramagnetic Resonance Image Reconstruction with Total
Variation Regularization, Image Processing On Line, 13 (2023), pp.
90–139. https://doi.org/10.5201/ipol.2023.414
Abstract
This work focuses on the reconstruction of two and three dimensional
images of the concentration of paramagnetic species from electron
paramagnetic resonance (EPR) measurements. A direct operator, modeling
how the measurements are related to the paramagnetic sample to be
imaged, is derived in the continuous framework taking into account the
physical phenomena at work during the acquisition process. Then, this
direct operator is discretized to closely take into account the discrete
nature of the measurements and provide an explicit link between them and
the discrete image to be reconstructed. A variational inverse problem
with total variation regularization is formulated and an efficient
resolvant scheme is implemented. The setting of the reconstruction
parameters is thoroughly studied and facilitated thanks to the
introduction of appropriate normalization factors. Moreover, an a
contrario algorithm is proposed to derive the optimal resolution at
which the data should be acquired. Finally, an in-depth experimental
study over real EPR datasets is done to illustrate the potential and
limitations of the presented image reconstruction model.
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