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20212025
most citedPatch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients

6 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2025

OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection

Nicolas Pinon, Robin Trombetta, Carole Lartizien

Unsupervised anomaly detection (UAD) aims to detect anomalies without labeled data, a necessity in many machine learning applications where anomalous samples are rare or not availa…

eess.IV2025

GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models

Daria Zotova, Nicolas Pinon, Robin Trombetta +3

Background and Objective. Research in the cross-modal medical image translation domain has been very productive over the past few years in tackling the scarce availability of large…

cs.CV2023

Anomaly detection in image or latent space of patch-based auto-encoders for industrial image analysis

Nicolas Pinon, Robin Trombetta, Carole Lartizien

We study several methods for detecting anomalies in color images, constructed on patch-based auto-encoders. Wecompare the performance of three types of methods based, first, on the…

eess.IV2023★ 2 cited

One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities

Nicolas Pinon, Robin Trombetta, Carole Lartizien

Anomaly detection remains a challenging task in neuroimaging when little to no supervision is available and when lesions can be very small or with subtle contrast. Patch-based repr…

eess.IV2023

Brain subtle anomaly detection based on auto-encoders latent space analysis : application to de novo parkinson patients

Nicolas Pinon, Geoffroy Oudoumanessah, Robin Trombetta +3

Neural network-based anomaly detection remains challenging in clinical applications with little or no supervised information and subtle anomalies such as hardly visible brain lesio…

eess.IV2021★ 6 cited

Patch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients

Verónica Muñoz-Ramírez, Nicolas Pinon, Florence Forbes +2

Although neural networks have proven very successful in a number of medical image analysis applications, their use remains difficult when targeting subtle tasks such as the identif…