Work

Unsupervised anomaly detection in brain FDG PET with deep generative models: An experimental analysis of model variability and mitigation strategies

Year: 2026

Type: conference-paper

Abstract: International audience

Source: HAL (Le Centre pour la Communication Scientifique Directe)

Authors: Solal, Maëlys, André, Pascaline, Burgos, Ninon

Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Inserm, Sorbonne Université, Assistance Publique – Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Institut du Cerveau

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Foundation for the National Institutes of Health, Alzheimer's Disease Neuroimaging Initiative, Northern California Institute for Research and Education, European Commission, Agence Nationale de la Recherche, Grand Équipement National De Calcul Intensif, National Institutes of Health, HORIZON EUROPE Framework Programme, Canadian Institutes of Health Research

Awards: G1190173965, G1258743643, PR[AI]RIE-PSAI - Paris School of Artificial Intelligence, G3010527862, G3103753459, G4079001475, G4950536974, G5235017436, PaRis Artificial Intelligence Research InstitutE, Center for Artificial Intelligence and Quantum Computing in System Brain Research, G7240651115, Anomaly Detection in Multimodal Neuroimaging for the Computer-aided Diagnosis of Dementia, G9000055340, G986930500

OpenAlex ID: W7103761575

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