Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution. - Cosmin Bercea; Andreas K. Maier; Thomas Köhler 004 (ICIP, 2016)

SHAMANN: Shared Memory Augmented Neural Networks. - Cosmin I. Bercea; Olivier Pauly; Andreas K. Maier; Florin C. Ghesu (IPMI, 2019)

FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation. - Cosmin I. Bercea; Benedikt Wiestler; Daniel Rueckert; Shadi Albarqouni (CoRR, 2021)

What do we learn? Debunking the Myth of Unsupervised Outlier Detection. - Cosmin I. Bercea; Daniel Rueckert; Julia A. Schnabel (CoRR, 2022)

Federated disentangled representation learning for unsupervised brain anomaly detection. - Cosmin I. Bercea; Benedikt Wiestler; Daniel Rueckert; Shadi Albarqouni (Nat. Mach. Intell., 2022)

Bias in Unsupervised Anomaly Detection in Brain MRI. - Cosmin I. Bercea; Esther Puyol-Antón; Benedikt Wiestler; Daniel Rueckert; Julia A. Schnabel; Andrew P. King (CLIP/FAIMI/EPIMI@MICCAI, 2023)

What Do AEs Learn? Challenging Common Assumptions in Unsupervised Anomaly Detection. - Cosmin I. Bercea; Daniel Rueckert; Julia A. Schnabel (MICCAI (5), 2023)

Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection. - Cosmin I. Bercea; Benedikt Wiestler; Daniel Rueckert; Julia A. Schnabel (MICCAI (5), 2023)

Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI. - Daniel M. Lang 003; Eli Schwartz; Cosmin I. Bercea; Raja Giryes; Julia A. Schnabel (CaPTion@MICCAI, 2023)

Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening. - Cosmin I. Bercea; Benedikt Wiestler; Daniel Rueckert; Julia A. Schnabel (MIDL, 2023)

Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion Models. - Cosmin I. Bercea; Michael Neumayr; Daniel Rueckert; Julia A. Schnabel (CoRR, 2023)

Attribute Regularized Soft Introspective Variational Autoencoder for Interpretable Cardiac Disease Classification. - Maxime Di Folco; Cosmin I. Bercea; Julia A. Schnabel (CoRR, 2023)

MedEdit: Counterfactual Diffusion-Based Image Editing on Brain MRI. - Malek Ben Alaya; Daniel M. Lang 003; Benedikt Wiestler; Julia A. Schnabel; Cosmin I. Bercea (SASHIMI@MICCAI, 2024)

Diffusion Models with Implicit Guidance for Medical Anomaly Detection. - Cosmin I. Bercea; Benedikt Wiestler; Daniel Rueckert; Julia A. Schnabel (MICCAI (11), 2024)

Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting. - Alicia Durrer; Julia Wolleb; Florentin Bieder; Paul Friedrich 002; Lester Melie-García; Mario Ocampo-Pineda; Cosmin I. Bercea; Ibrahim Ethem Hamamci; Benedikt Wiestler; Marie Piraud; Özgür Yaldizli; Cristina Granziera; et al. (DGM4MICCAI@MICCAI, 2024)

Interpretable Representation Learning of Cardiac MRI via Attribute Regularization. - Maxime Di Folco; Cosmin I. Bercea; Emily Chan; Julia A. Schnabel (MICCAI (10), 2024)

Language Models Meet Anomaly Detection for Better Interpretability and Generalizability. - Jun Li; Su Hwan Kim 007; Philip Müller; Lina Felsner; Daniel Rueckert; Benedikt Wiestler; Julia A. Schnabel; Cosmin I. Bercea (LDTM/MMMI/ML4MHD/ML-CDS@MICCAI, 2024)

Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound. - Hanna Mykula; Lisa Gasser; Silvia Lobmaier; Julia A. Schnabel; Veronika A. M. Zimmer; Cosmin I. Bercea (ASMUS@MICCAI, 2024)

Towards Universal Unsupervised Anomaly Detection in Medical Imaging. - Cosmin I. Bercea; Benedikt Wiestler; Daniel Rueckert; Julia A. Schnabel (CoRR, 2024)

Multi-Image Visual Question Answering for Unsupervised Anomaly Detection. - Jun Li; Cosmin I. Bercea; Philip Müller; Lina Felsner; Su Hwan Kim 007; Daniel Rueckert; Benedikt Wiestler; Julia A. Schnabel (CoRR, 2024)

Interpretable Representation Learning of Cardiac MRI via Attribute Regularization. - Maxime Di Folco; Cosmin I. Bercea; Julia A. Schnabel (CoRR, 2024)

Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders. - Mehmet Yigit Avci; Emily Chan; Veronika A. M. Zimmer; Daniel Rueckert; Benedikt Wiestler; Julia A. Schnabel; Cosmin I. Bercea (CoRR, 2024)

FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks. - Peiran Wu; Che Liu; Canyu Chen; Jun Li; Cosmin I. Bercea; Rossella Arcucci (CoRR, 2024)

Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representations. - Sameer Ambekar; Julia A. Schnabel; Cosmin I. Bercea (CoRR, 2024)

Denoising Diffusion Models for Anomaly Localization in Medical Images. - Cosmin I. Bercea; Philippe C. Cattin; Julia A. Schnabel; Julia Wolleb (CoRR, 2024)

Enhancing Abnormality Grounding for Vision Language Models with Knowledge Descriptions. - Jun Li; Che Liu; Wenjia Bai; Rossella Arcucci; Cosmin I. Bercea; Julia A. Schnabel (CoRR, 2025)

Semantic Alignment of Unimodal Medical Text and Vision Representations. - Maxime Di Folco; Emily Chan; Marta Hasny; Cosmin I. Bercea; Julia A. Schnabel (CoRR, 2025)

NOVA: A Benchmark for Anomaly Localization and Clinical Reasoning in Brain MRI. - Cosmin I. Bercea; Jun Li; Philipp Raffler; Evamaria O. Riedel; Lena Schmitzer; Angela Kurz; Felix Bitzer; Paula Roßmüller; Julian Canisius; Mirjam L. Beyrle; Che Liu; Wenjia Bai; et al. (CoRR, 2025)

Knowledge to Sight: Reasoning over Visual Attributes via Knowledge Decomposition for Abnormality Grounding. - Jun Li; Che Liu; Wenjia Bai; Mingxuan Liu; Rossella Arcucci; Cosmin I. Bercea; Julia A. Schnabel (CoRR, 2025)