Stacked PointNets for alignment of particles with cylindrical symmetry in single molecule localization microscopy - Ecole Nationale du Génie de l'Eau et de l'Environnement de Strasbourg Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

Stacked PointNets for alignment of particles with cylindrical symmetry in single molecule localization microscopy

Résumé

Single molecule localization microscopy is an essential observation tool in biology that yields data in the form of point clouds. It is still limited by an anisotropic resolution and inhomogeneous labeling density. This issue can be addressed by reconstructing a single model from multiple aligned copies of the same particle. However, generic registration methods fail to align point clouds in the presence of anisotropic noise and outliers. Therefore, we propose an alignment method dedicated to a common type of particle geometry, namely cylindrical symmetry. We focus on the centriole, a fundamental macromolecular assembly with ninefold cylindrical symmetry. We design a neural network based on stacked PointNet architectures that estimates the center and axis of symmetry of individual particles in SMLM, in order to align them in the same canonical space. We demonstrate the robustness of our approach on simulated and real dSTORM data.
Fichier principal
Vignette du fichier
ISBI_Fan_final.pdf (3.32 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03453438 , version 1 (28-11-2021)

Identifiants

Citer

Youbo Fan, Sylvain Faisan, Étienne Baudrier, Fabian Zwettler, Markus Sauer, et al.. Stacked PointNets for alignment of particles with cylindrical symmetry in single molecule localization microscopy. International Symposium on Biomedical Imaging, Apr 2021, Nice, France. ⟨10.1109/ISBI48211.2021.9434116⟩. ⟨hal-03453438⟩
45 Consultations
28 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More