« avril 2024 »
1 2 3 4 5 6 7
8 9 10 11 12 13 14
15 16 17 18 19 20 21
22 23 24 25 26 27 28
29 30 1 2 3 4 5
Tous les évènements de Physique à venir

Tous les évènements de Biologie / Chimie à venir

Tous les évènements à venir

Les évènements relevant de la Physique et de la Biologie / Chimie sont représentés en turquoise

Phase retrieval in X-ray phase contrast imaging using deep learning

Lundi 4 décembre 2023 14:00 - Duree : 1 heure
Lieu : Conference room 2nd floor - LIPhy - 140 Avenue de la Physique - St Martin d’Hères + VISIO-CONFERENCE

Orateur : Max LANGER (TIMC, CNRS, UGA)

You can attend the seminar in the LIPhy conference room or you can follow the live stream :

https://meet.univ-grenoble-alpes.fr/b/rom-l57-idw-8wr. The link will be activated shortly before the seminar.

Résumé :

X-ray in-line phase contrast imaging is a highly sensitive imaging technique relying on the coherence of the beam to achieve contrast through interference. The development of high-flux X-ray sources has considerably advanced phase contrast imaging, pushing the attainable resolution below 40 nm in 3D and finding applications in a variety of fields. While phase-contrast imaging relies on the phase shift of the beam induced by the sample, only the intensity of the beam can be measured. Thus, the phase information is lost and must be estimated from one or several intensity images through a process called phase retrieval. Here, we consider relatively short propagation distances. Phase retrieval in this context is a nonlinear ill-posed inverse problem. Various methods have been proposed to retrieve the phase, either by linearizing the problem to obtain an analytical solution or by iterative algorithms. Recently, deep-learning techniques have yielded advances in several image processing task, specifically in inverse problems and image reconstruction. In this talk, I present our developments of deep learning-based approaches for the phase retrieval problem in in-line phase contrast, where we aim to overcome the limitations of classical approaches, such as restrictive assumptions on the forward model, the choice regularization and a priori knowledge, and the computation time.

Contact : aurelien.gourrier@univ-grenoble-alpes.fr

Discipline évènement : (Physique)
Entité organisatrice : (LIPhy)
Nature évènement : (Séminaire)
Site de l'évènement : Domaine Universitaire de St Martin d’Hères

Prévenir un ami par email

Télécharger dans mon agenda

Cafés sciences de Grenoble | UdPPC de Grenoble | Sauvons Le Climat | Cafe des sciences de Vizille
Accueil du site | Secretariat | Espace privé | Suivre la vie du site RSS 2.0 : Tous les evenements Suivre la vie du site RSS 2.0 : Evenements de Physique Suivre la vie du site RSS 2.0 : Evenements de Biologie & Chimie