Cardiac Motion Modeling with Parallel Transport and Shape Splines

no code implementations • 17 Feb 2021 • Nicolas Guigui, Pamela Moceri, Maxime Sermesant, Xavier Pennec

In cases of pressure or volume overload, probing cardiac function may be difficult because of the interactions between shape and deformations. In this work, we use the LDDMM framework and parallel transport to estimate and reorient deformations of the right ventricle.

Classifying histograms of medical data using information geometry of beta distributions

no code implementations • 3 Jun 2020 • Alice Le Brigant, Nicolas Guigui, Sana Rebbah, Stéphane Puechmorel

In this paper, we use tools of information geometry to compare, average and classify histograms.

Geomstats: A Python Package for Riemannian Geometry in Machine Learning

1 code implementation • ICLR 2019 • Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan Holmes, Xavier Pennec

We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matrices, Lie groups of transformations, and many more.

BIG-bench Machine Learning Clustering +2