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

Abstract

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.

Four-dimensional reconstruction and characterization of bladder deformations

“…Besides, future studies will be conducted with the ethical authorization to inject extrageneous liquid into the rectal and vaginal cavities in order to segment all pelvic organs and study the complete pelvic dynamics. The ability to now obtain dynamic 3D volumes allows the development of more advanced 3D shape descriptors [41] to better characterize the degree of severity of a pathology for diagnostic assistance. These studies are a 3D extension of descriptors such as we already proposed for 2D dynamic pelvic acquisitions [8].…”

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

“…Promising results were obtained, showing the bladder in its 3D complexity during deformation due to strain conditions with an estimation of the most deformed tissue areas. These high-resolution temporal data are then employed to introduce a compact characterization of bladder surfaces in [30].…”