Understanding digital shapes from the life sciences
t-LiDAR point cloud filtering for forest tree reconstruction
We analyze and filter or correct the noise in t-LiDAR point clouds due to multiple hits of a laser beam with the scene. We use the cleaned point cloud to enhance forest tree reconstruction methods.
|Context:||Romain Rombourg's Master then PhD thesis and Digitree project.|
|Co-workers:||Romain Rombourg (Master then PhD student), Eric Casella (researcher, Forest Research UK).|
|More details:||[FSPMA'16a], [FSPMA'16b].|
Plant clustering into elementary units
We propose a spectral clustering approach to segment a 3D point cloud of a plant (typically acquired with a laser scanner device) into elementary units (branches, petioles, leaves).
|Co-workers:||Eric Casella (researcher, Forest Research UK), Rémy Cumont (intern), Dobrina Boltcheva (postdoc).|
|More details:||[FSPM'13], [IJRS'16].|
Ontology-based anatomical segmentation
To automatically segment a 3D mesh of a human organ into anatomical meaningful parts, we propose to benefit from standardized anatomy information, organized in an ontology (for instance myCorporisFabrica).
|Context:||Sahar Hassan's PhD thesis.|
|Co-workers:||Sahar Hassan (PhD student), Georges-Pierre Bonneau (professor, Univ. Grenoble), Olivier Palombi (neurosurgeon and assistant professor, Univ. Grenoble).|
Automatic cerebral aneurysm localization and quantification
We propose a simple method to detect, locate and quantify the size and shape of aneurysms on blood vessels, to help neurosurgeons before operation.
|Context:||Sahar Hassan's Master and PhD theses.|
|Co-workers:||Sahar Hassan (Master then PhD student), François Faure (assistant professor, Univ. Grenoble), Olivier Palombi (neurosurgeon and assistant professor, Univ. Grenoble).|