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Found 6 papers, 0 papers with code
Temporal and volumetric denoising via quantile sparse image prior
For the purpose of denoising, we propose a variational framework based on the QuaSI prior and a Huber data fidelity model that can handle 3-D and 3-D+t data.
QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data
Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise.
Mixed one-bit compressive sensing with applications to overexposure correction for CT reconstruction
Aiming at overexposure correction for computed tomography (CT) reconstruction, we in this paper propose a mixed one-bit compressive sensing (M1bit-CS) to acquire information from both regular and saturated measurements.
A Self-Taught Artificial Agent for Multi-Physics Computational Model Personalization
Then Vito was applied to the inverse problem of cardiac electrophysiology and the personalization of a whole-body circulation model.
Super-Resolved Retinal Image Mosaicing
The acquisition of high-resolution retinal fundus images with a large field of view (FOV) is challenging due to technological, physiological and economic reasons.
3-D/2-D Registration of Cardiac Structures by 3-D Contrast Agent Distribution Estimation
Using a combination of both methods, our evaluation on 11 well-contrasted clinical datasets yielded an error of 7. 9+/-6. 3 mm over all frames.
