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Publications associées (133)

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Amsterdam2024

Functionalization of harmonic nanoparticles for drug release and multimodal imaging applications

Adrian Stefan Gheata

Cancer is among the leading causes of death worldwide, and as knowledge of the disease continues to grow there is an increasing interest towards precision medicine: more specifically towards the theranostics field, i.e the development of targeted molecular ...

EPFL2024

Characterization of a flexible a-Si:H detector for in vivo dosimetry in therapeutic x-ray beams

Sylvain Dunand, Jonathan Emanuel Thomet, Luca Massimiliano Antognini, Matthew James Large

BackgroundThe increasing use of complex and high dose-rate treatments in radiation therapy necessitates advanced detectors to provide accurate dosimetry. Rather than relying on pre-treatment quality assurance (QA) measurements alone, many countries are now ...

Hoboken2024

Impact of CO2-rich seawater injection on the flow properties of basalts

Lyesse Laloui, Eleni Stavropoulou, Cesare Griner

Permanent CO storage in basalts through mineralisation offers a promising solution for reducing carbon emissions and mitigating climate change. This study focuses on the impact of potential mineralisation on the flow properties of the basaltic material. Fl ...

2024

Unveiling breast cancer metastasis through an advanced X-ray imaging approach

Marianne Liebi

Breast cancer is a significant global health burden, causing a substantial number of deaths. Systemic metastatic tumour cell dissemination is a major cause of poor outcomes. Understanding the mechanisms underlying metastasis is crucial for effective interv ...

Berlin2024

Effect of wettability and textile architecture on fluid displacement and pore formation during infiltration of carbon fibrous preforms

Véronique Michaud, Baris Çaglar, Helena Luisa Teixido Pedarros

We seek to address how air entrapment mechanisms during infiltration are influenced by the wetting characteristics of the fluid and the pore network formed by the reinforcement. To this end, we evaluated the behavior of two model fluids with different surf ...

London2023

Measurement and modelling of dynamic fluid saturation in carbon reinforcements

Véronique Michaud, Baris Çaglar, Helena Luisa Teixido Pedarros, Guillaume Clément Broggi

We propose a methodology to monitor the progressive saturation of a non-translucent unidirectional carbon fabric stack through its thickness by means of X-ray radiography and extract the dynamic saturation curves using image analysis. Four constant flow ra ...

2023

Clinical efficacy of ONC201 in H3K27M-mutant diffuse midline gliomas is driven by disruption of integrated metabolic and epigenetic pathways

Sebastian Martin Waszak, Li Jiang

H3K27M-mutant diffuse midline glioma (DMG) patients have no proven effective therapies. ONC201 has recently demonstrated efficacy in these patients, but the mechanism behind this remains unknown. We assessed clinical outcomes, tumor sequencing, and tissue/ ...

2023

A review of materials used in tomographic volumetric additive manufacturing

Christophe Moser, Jorge Andres Madrid Wolff, Riccardo Rizzo

Volumetric additive manufacturing is a novel fabrication method allowing rapid, freeform, layer-less 3D printing. Analogous to computer tomography (CT), the method projects dynamic light patterns into a rotating vat of photosensitive resin. These light pat ...

SPRINGER HEIDELBERG2023

Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

Robustness of medical image classification models is limited by its exposure to the candidate disease classes. Generalized zero shot learning (GZSL) aims at correctly predicting seen and unseen classes and most current GZSL approaches have focused on the s ...

Cham2023

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