A novel generic dictionary-based denoising method for improving noisy and densely packed nuclei segmentation in 3D time-...
International audience
Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI
We propose to learn a probabilistic motion model from a sequence of images. Besides spatio-temporal registration, our method offers to predict motion from a limited number of frames, useful for temporal super-resolution. The model is based on a probabilistic latent space and a novel temporal dropout training scheme. This enables simulation and inte...
Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI
We propose to learn a probabilistic motion model from a sequence of images. Besides spatio-temporal registration, our method offers to predict motion from a limited number of frames, useful for temporal super-resolution. The model is based on a probabilistic latent space and a novel temporal dropout training scheme. This enables simulation and inte...
Auto-encoding meshes of any topology with the current-splatting and exponentiation layers
Deep learning has met key applications in image computing, but still lacks processing paradigms for meshes, i.e. collections of elementary geometrical parts such as points, segments or triangles. Meshes are both a powerful representation for geometrical objects, and a challenge for network architectures because of their inherent irregular structure...
Coarse-to-Fine Registration of Airborne LiDAR Data and Optical Imagery on Urban Scenes
Applications based on synergistic integration of optical imagery and LiDAR data are receiving a growing interest from the remote sensing community. However, a misaligned integration between these datasets may fail to fully profit the potential of both sensors. In this regard, an optimum fusion of optical imagery and LiDAR data requires an accurate ...
3D Flow Field Estimation and Assessment for Live Cell Fluorescence Microscopy
Motivation: The revolution in light sheet microscopy enables the concurrent observation of thousands of dynamic processes, from single molecules to cellular organelles, with high spatiotemporal resolution. However, challenges in the interpretation of multidimensional data requires the fully automaticmeasurement of those motions to link local proces...
New Insights on the Optimality Conditions of the l2-l0 Minimization Problem
This paper is devoted to the analysis of necessary (not sufficient) optimality conditions for the l0-regularized least-squares minimization problem. Such conditions are the roots of the plethora of algorithms that have been designed to cope with this NP-hard problem. Indeed, as global optimality is, in general, intractable, these algorithms only en...
Removing non-signicant regions in hierarchical clustering and segmentation
We propose an efficient algorithm that removes unimportant regions from a hierarchical partition tree, while preserving the hierarchical partition structure. Various experiments demonstrate that applying this algorithm on various classification or segmentation problems does indeed improve the results by a large margin. Code is available online at h...
Can Avalanche Deposits be Effectively Detected by Deep Learning on Sentinel-1 Satellite SAR Images?
Achieving reliable observations of avalanche debris is crucial for many applications including avalanche forecasting. The ability to continuously monitor the avalanche activity, in space and time, would provide indicators on the potential instability of the snowpack and would allow a better characterization of avalanche risk periods and zones. In t...
Efficient position estimation of 3D fluorescent spherical beads in confocal microscopy via Poisson denoising
Particle estimation is a classical problem arising in many science fields, such as biophysics, fluid mechanics, bio-medical imaging. Many interesting applications in these areas involve 3D imaging data: this work presents a technique to estimate the 3D coordinates of the center of spherical particles. This procedure has its core in the processing o...
