Robust vascular network extractionand understanding within hepatic biomedical images Consult publications
Our research project
Cardiovascular diseases and other blood vessels disorders increase in the world-wide scale and in particular in Occident. The evolution of computer science in researches investigating vascular networks has raised the interest in numerical reconstructing and understanding of those complex tree-like structures. The R-VESSEL-X project proposes original and robust developments of image analysis and machine learning algorithms integrating strong mathematical frameworks, e.g. digital geometry and topology, mathematical morphology, or graphs for reconstructing vessels of the liver beyong medical image content. Another objective of R-VESSEL-X is to diffuse research works in an open-source way, with the developments of plug-ins compatible with the ITK and VTK librairies largely popularized by the KITWARE company. This project will also include benchmarks composed of images, associated ground-truth and quality metrics, so that researchers and engineers evaluate their novel contributions. The consortium of R-VESSEL-X is composed of the following laboratories: Institut Pascal (coordinator, Le Puy-en-Velay/Clermont-Ferrand), LIRIS (Lyon), CReSTIC (Reims), working together with the KITWARE company (Lyon). This is a highly pluridisciplinary group composed of researchers in computer science-related topics (biomedical image processing, numerical simulation and analysis), applied mathematics (digital geometry and topology, mathematical morphology), working with medical doctors (radiologists, hepatologists) and young researchers and developers enrolled for the project.
R-Vessel-X shares open-source codes
Abstract: Component-trees are classical tree structures for grey-level image modelling. Component graphs are defined as a generalization of component trees to images taking their values in any (totally or partially) ordered sets. Similarly to component-trees,...