29 citations · 52 across the 10 of their papers we have counts for
5 papers · 1 filter
Compartment model-based nonlinear unmixing for kinetic analysis of dynamic PET images
Yanna Cruz Cavalcanti, Thomas Oberlin, Vinicius Ferraris +3
When no arterial input function is available, quantification of dynamic PET images requires a previous step devoted to the extraction of a reference time-activity curve (TAC). Fact…
Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling
Etienne Monier, Thomas Oberlin, Nathalie Brun +3
This paper discusses the reconstruction of partially sampled spectrum-images to accelerate the acquisition in scanning transmission electron microscopy (STEM). The problem of image…
Factor analysis of dynamic PET images: beyond Gaussian noise
Yanna Cruz Cavalcanti, Thomas Oberlin, Nicolas Dobigeon +4
Factor analysis has proven to be a relevant tool for extracting tissue time-activity curves (TACs) in dynamic PET images, since it allows for an unsupervised analysis of the data.…
Coupled dictionary learning for unsupervised change detection between multi-sensor remote sensing images
Vinicius Ferraris, Nicolas Dobigeon, Yanna Cavalcanti +2
Archetypal scenarios for change detection generally consider two images acquired through sensors of the same modality. However, in some specific cases such as emergency situations,…
Reconstruction of partially sampled multi-band images - Application to STEM-EELS imaging
Étienne Monier, Thomas Oberlin, Nathalie Brun +3
Electron microscopy has shown to be a very powerful tool to map the chemical nature of samples at various scales down to atomic resolution. However, many samples can not be analyze…