Publications associées à Bulged Eardrum Detection From 3D Data

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

We propose an image-based elastography method to measure the heterogeneous stiffness inside a cell and its nucleus. It uses a widely accessible setup consisting of plate compression imaged with fluorescence microscopy. Our framework recovers a spatial map ...

IEEE2023

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Gulnaz Ganeeva

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

EPFL2023

Image-based geometric digital twinning for stone masonry elements

Katrin Beyer, Bryan German Pantoja Rosero, Savvas Saloustros

We present an image-based pipeline for generating geometrical digital twins (GDTs) of stone masonry elements with detail down to the stone level. For this purpose, we acquire RGB images of the individual stones and of the wall during the construction phase ...

2022

Self-morphing Soft Parallel-and-coplanar Electroadhesive Grippers Based on Laser-scribed Graphene Oxide Electrodes

Djen Timo Kühnel

Electroadhesion is a versatile and controllable adhesion mechanism that has been used extensively in robotics. Soft electroadhesion embodies electrostatic adhesion in soft materials and is required for shape-adaptive and safe grasping of curved objects and ...

IEEE2022

Efficient lattice Green's function method for bounded domain problems

William Curtin, Max Ludwig Hodapp, Ankit Gupta

The lattice Green's function method (LGFM) is the discrete counterpart of the continuum boundary element method and is a natural approach for solving intrinsically discrete solid mechanics problems that arise in atomistic-continuum coupling methods. Here, ...

Wiley2022

Sound and Complete Verification of Polynomial Networks

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Mehmet Fatih Sahin, Elias Abad Rocamora

Polynomial Networks (PNs) have demonstrated promising performance on face and image recognition recently. However, robustness of PNs is unclear and thus obtaining certificates becomes imperative for enabling their adoption in real-world applications. Exist ...

2022

A lattice Boltzmann model for self-diffusiophoretic particles near and at liquid-liquid interfaces

Ignacio Pagonabarraga Mora

We introduce a novel mesoscopic computational model based on a multiphase-multicomponent lattice Boltzmann method for the simulation of self-phoretic particles in the presence of liquid-liquid interfaces. Our model features fully resolved solvent hydrodyna ...

AIP Publishing2022

Derivative voltammetry: a simple tool to probe reaction selectivity in photoelectrochemical cells

Kevin Sivula, Florent Alexandre Boudoire, Nukorn Plainpan

We demonstrate the use of the derivative voltammogram method to predict the selectivity of the photo-driven oxidation of 5-hydroxymethylfurfural (HMF) on a WO3 photoanode as a function of applied potential using only information obtained from the linear sw ...

2022

Design and modelling of a compliant constant-force surgical tool for objective assessment of ossicular chain mobility

Simon Nessim Henein, Charles Baur, Loïc Benoît Tissot-Daguette

Surgeons generally assess the mobility of the ossicle chain by manual palpation using rigid elongated hooks inserted through the ear canal. As the applied forces are in the range of a few grams equivalent force, the measurement remains subjective and its r ...

IEEE2021

Variants in USP48 encoding ubiquitin hydrolase are associated with autosomal dominant non-syndromic hereditary hearing loss

Nicolas Jean Philippe Guex

Non-Syndromic Hereditary Hearing Loss (NSHHL) is a genetically heterogeneous sensory disorder with about 120 genes already associated. Through exome sequencing (ES) and data aggregation, we identified a family with six affected individuals and one unrelate ...

Oxford University Press2021