arXiv subjects

Karim Makki

Publications and source records attributed to Karim Makki.

6 recordsLinked to original sources

arXiv2023

Reconstructing the normal and shape at specularities in endoscopy

Specularities are numerous in endoscopic images. They occur as many white small elliptic spots, which are generally ruled out as nuisance in image analysis and computer vision methods. Instead, we propose to use specularities as cues for 3D perception. Specifically, we propose a new method to reconstruct, at each specularity, the observed tissue's normal direction (i.e., its orientation) and shape (i.e., its curvature) from a single image. We show results on simulated and real interventional images.

cs.CV↗

arXiv2023

Normal reconstruction from specularity in the endoscopic setting

We show that for a plane imaged by an endoscope the specular isophotes are concentric circles on the scene plane, which appear as nested ellipses in the image. We show that these ellipses can be detected and used to estimate the plane's normal direction, forming a normal reconstruction method, which we validate on simulated data. In practice, the anatomical surfaces visible in endoscopic images are locally planar. We use our method to show that the surface normal can thus be reconstructed for each of the numerous specularities typically visible on moist tissues. We show results on laparoscopic and colonoscopic images.

cs.CV↗

arXiv2022

Level set based particle filter driven by optical flow: an application to track the salt boundary from X-ray CT time-series

Image-based computational fluid dynamics have long played an important role in leveraging knowledge and understanding of several physical phenomena. In particular, probabilistic computational methods have opened the way to modelling the complex dynamics of systems in purely random turbulent motion. In the field of structural geology, a better understanding of the deformation and stress state both within the salt and the surrounding rocks is of great interest to characterize all kinds of subsurface long-terms energy-storage systems. The objective of this research is to determine the non-linear deformation of the salt boundary over time using a parallelized, stochastic filtering approach from x-ray computed tomography (CT) image time series depicting the evolution of salt structures triggered by gravity and under differential loading. This work represents a first step towards bringing together physical modeling and advanced stochastic image processing methods where model uncertainty is taken into account.

cs.CV↗

arXiv2021

Characterization of surface motion patterns in highly deformable soft tissue organs from dynamic MRI: An application to assess 4D bladder motion

Dynamic MRI may capture temporal anatomical changes in soft tissue organs with high contrast but the obtained sequences usually suffer from limited volume coverage which makes the high resolution reconstruction of organ shape trajectories a major challenge in temporal studies. Because of the variability of abdominal organ shapes across time and subjects, the objective of this study is to go towards 3D dense velocity measurements to fully cover the entire surface and to extract meaningful features characterizing the observed organ deformations and enabling clinical action or decision. We present a pipeline for characterization of bladder surface dynamics during deep respiratory movements. For a compact shape representation, the reconstructed temporal volumes were first used to establish subject-specific dynamical 4D mesh sequences using the LDDMM framework. Then, we performed a statistical characterization of organ dynamics from mechanical parameters such as mesh elongations and distortions. Since we refer to organs as non flat surfaces, we have also used the mean curvature changes as metric to quantify surface evolution. However, the numerical computation of curvature is strongly dependant on the surface parameterization. To cope with this dependency, we employed a new method for surface deformation analysis. Independent of parameterization and minimizing the length of the geodesic curves, it stretches smoothly the surface curves towards a sphere by minimizing a Dirichlet energy. An Eulerian PDE approach is used to derive a shape descriptor from the curve-shortening flow. Intercorrelations between individual motion patterns are computed using the Laplace Beltrami operator eigenfunctions for spherical mapping. Application to extracting characterization correlation curves for locally controlled simulated shape trajectories demonstrates the stability of the proposed shape descriptor.

cs.CV↗

arXiv2020

The power spectrum extended technique applied to images of binary stars in the infrared

We recently proposed a new lucky imaging technique, the Power Spectrum Extended (PSE), adapted for image reconstruction of short-exposure astronomical images in case of weak turbulence or partial adaptive optics correction. In this communication we show applications of this technique to observations of about 30 binary stars in H band with the 1m telescope of the Calern C2PU observatory. We show some images reconstructed at the diffraction limit of the telescope and provide measurements of relative astrometry and photometry of observed couples.

astro-ph.IM↗

arXiv2020

A new geodesic-based feature for characterization of 3D shapes: application to soft tissue organ temporal deformations

In this paper, we propose a method for characterizing 3D shapes from point clouds and we show a direct application on a study of organ temporal deformations. As an example, we characterize the behavior of a bladder during a forced respiratory motion with a reduced number of 3D surface points: first, a set of equidistant points representing the vertices of quadrilateral mesh for the surface in the first time frame are tracked throughout a long dynamic MRI sequence using a Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework. Second, a novel geometric feature which is invariant to scaling and rotation is proposed for characterizing the temporal organ deformations by employing an Eulerian Partial Differential Equations (PDEs) methodology. We demonstrate the robustness of our feature on both synthetic 3D shapes and realistic dynamic MRI data portraying the bladder deformation during forced respiratory motions. Promising results are obtained, showing that the proposed feature may be useful for several computer vision applications such as medical imaging, aerodynamics and robotics.

cs.CV↗