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Last name: ORLHAC
First name: Fanny
International audience
International audience
Abstract Nonbiological differences related to CT scanner type can be removed from radiomic feature values, allowing radiomics features to be combined in multicenter or multivendor studies.Background Radiomics extracts features from medical images more precisely and more accurately than visual assessment. However, radiomics features are affected...
Abstract Purpose FDOPA PET shows good performance for the diagnosis of striatal dopaminergic denervation, making it a valuable tool for the differential diagnosis of Parkinsonism. Textural features are image biomarkers that could potentially improve the early diagnosis and monitoring of neurodegenerative parkinsonian syndromes. We explored the...
International audience
Objective: The characterization of tumor heterogeneity using radiomic features from PET images is gaining interest in the context of precision medicine. Yet, the relationship between radiomic features and biological characteristics of lesions needs to be clarified. To this end, we studied the relationship between PET radiomic features and...
Objectif : La caractérisation de l'hétérogénéité tumorale à partir des images TEP connaît un intérêt croissant. Or le lien entre les variables radiomiques (VR) et les caractéristiques biologiques des lésions est encore mal connu. Notre objectif est d'étudier la corrélation entre les VR et les variables métabolomiques (VM) dans le cancer du...
La caractérisation de l'hétérogénéité tumorale à partir des images médicales (appeléeaussi radiomique) et de l'extraction de données omiques est un enjeu majeur en cancérologie,notamment dans la mise en place de la médecine de précision. Or actuellement, le lien entre lesvariables radiomiques (VR) et les caractéristiques biologiques des lésions...
Purpose: The aim of this study was to compare the performance and added clinical value of a semiautomated radiomics model and an automated 3dimensinal convolutional neural network (3D-CNN) model for diagnosing neurodegenerative parkinsonian syndromes on 18 F-FDOPA PET images. Patients and Methods: This 2-center retrospective study included 687...
Aim/Introduction: The design and validation of a reliable radiomic signature is challenging when few patients are available because the disease is rare, the imaging protocol is specific and/or the classes are unbalanced. In this context, we propose an approach to identify a signature and estimate its reliability. Materials and Methods: 84...
En imagerie TEP, les études multicentriques sont limitées car les mesures effectuées sur les images (SUV et autres index radiomiques) sont sensibles aux protocoles d'acquisition et de reconstruction. Notre but est de valider l'utilisation de la méthode d'harmonisation ComBat afin de supprimer l'« effet centre » dans les études multicentriques...
Objectives: Quantitative characterization of tumor heterogeneity using PET images shows encouraging results to predict patient response or survival, paving the way for precision medicine based on radiomic features. Yet, the vast majority of results are obtained in monocentric studies, without subsequent validation in multicenter settings. One...
International audience
Objectives: Most supervised learning approaches currently applied in radiomics consist in classifying patients in groups (eg, responder versus non-responder, short overall survival versus long overall survival). With these methods, individual information from each patient is used only to assign a patient to a group. To preserve detailed...
International audience
The real-world implementation of federated learning is complex and requires research and development actions at the crossroad between different domains ranging from data science, to software programming, networking, and security. While today several FL libraries are proposed to data scientists and users, most of these frameworks are not...