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Three-Dimensional Optical Diffraction Tomography with Lippmann-Schwinger Model
Thanh-an Pham, Emmanuel Soubies, Ahmed Ayoub +3
A broad class of imaging modalities involve the resolution of an inverse-scattering problem. Among them, three-dimensional optical diffraction tomography (ODT) comes with its own c…
Time-Dependent Deep Image Prior for Dynamic MRI
Jaejun Yoo, Kyong Hwan Jin, Harshit Gupta +3
We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study…
Method for Assessing the Fidelity of Optical Diffraction Tomography Reconstruction Methods
Ahmed B. Ayoub, Thanh-An Pham, Joowon Lim +2
We use a spatial light modulator in a diffraction tomographic system to assess the accuracy of different refractive index reconstruction algorithms. Optical phase conjugation princ…
Native Banach spaces for splines and variational inverse problems
Michael Unser, Julien Fageot
We propose a systematic construction of native Banach spaces for general spline-admissible operators . In short, the native space for and the (dual) norm $\|\cdo…
Dictionary Learning for Two-Dimensional Kendall Shapes
Anna Song, Virginie Uhlmann, Julien Fageot +1
We propose a novel sparse dictionary learning method for planar shapes in the sense of Kendall, namely configurations of landmarks in the plane considered up to similitudes. Our sh…
A unifying representer theorem for inverse problems and machine learning
Michael Unser
The standard approach for dealing with the ill-posedness of the training problem in machine learning and/or the reconstruction of a signal from a limited number of measurements is…