Eleven papers accepted at MICCAI Workshops 2024

Sameer Ambekar, Cosmin I. Bercea, Maxime Di Folco, Lina Felsner, Fryderyk Kögl, Daniel M. Lang, Jun Li, Richard Osuala, Anna Reithmeir, Anneliese Riess

Jul 5, 2024 2 min read

Selective Test-Time Adaptation using Neural Implicit Representations for Unsupervised Anomaly Detection
Sameer Ambekar, Julia Schnabel, and Cosmin I. Bercea.
[link will be available soon]
MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI
Malek Ben Alaya, Daniel M. Lang, Benedikt Wiestler, Julia A. Schnabel, and Cosmin I. Bercea
(https://arxiv.org/pdf/2407.15270)
Unsupervised Analysis of Alzheimer’s Disease Signatures using 3D Deformable Autoencoders
Mehmet Yigit Avci, Emily Chan, Veronika Zimmer, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel, and Cosmin I. Bercea
(https://arxiv.org/pdf/2407.03863)
On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models
Deniz Daum; Richard Osuala; Anneliese Riess; Georgios Kaissis; Julia A. Schnabel; Maxime Di Folco
(https://arxiv.org/abs/2407.16405)
Graph Neural Networks: A suitable alternative to MLPs in latent 3D medical image classification?
Johannes Kiechle, Daniel M. Lang, Stefan M. Fischer, Lina Felsner, Jan C. Peeken, Julia A. Schnabel
(http://arxiv.org/abs/2407.17219)
General Vision Encoder Features as Guidance in Medical Image Registration
Fryderyk Kögl, Anna Reithmeir, Vasiliki Sideri-Lampretsa, Ines Machado, Rickmer Braren, Daniel Rückert, Julia A Schnabel, Veronika A Zimmer
(https://arxiv.org/abs/2407.13311)
Language Models Meet Anomaly Detection for Better Interpretability and Generalizability
Jun Li, Su Hwan Kim, Philip Müller, Lina Felsner, Daniel Rueckert, Benedikt Wiestler, Julia A.Schnabel, and Cosmin I. Bercea
(https://arxiv.org/pdf/2404.07622v2)
A Self-Supervised Image Registration Approach for Measuring Local Response Patterns in Metastatic Ovarian Cancer
Inês P. Machado, Anna Reithmeir, Fryderyk Kogl, Leonardo Rundo, Gabriel Funingana, Marika Reinius, Gift Mungmeeprued, Zeyu Gao, Cathal McCague, Eric Kerfoot, Ramona Woitek, Evis Sala, Yangming Ou, James Brenton, Julia Schnabel, Mireia Crispin
(https://arxiv.org/abs/2407.17114)
Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound
Hanna Mykula, Lisa Gasser, Silvia Lobmaier, Julia A. Schnabel, Veronika Zimmer, and Cosmin I. Bercea
(https://arxiv.org/pdf/2407.15119)
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data
Richard Osuala, Daniel M. Lang, Anneliese Riess, Georgios Kaissis, Zuzanna Szafranowska, Grzegorz Skorupko, Oliver Diaz, Julia A. Schnabel, Karim Lekadir
(https://arxiv.org/abs/2407.12669)
Complex-valued Federated Learning with Differential Privacy and MRI Applications
Anneliese Riess, Alexander Ziller, Stefan Kolek, Daniel Rueckert, Julia Schnabel, Georgios Kaissis
([link will be available soon])

Sameer Ambekar

Doctoral Researcher

My research interests include Domain Generalization, Meta learning, Variational Inference

Cosmin I. Bercea

Research Scientist

I am a postdoctoral researcher specializing in vision and multimodal learning for medical image analysis, with the current focus on developing vision-language models for generative downstream tasks.

My research interest is the study of the cardiac function via machine learning methods, in particular representation learning methods that aim to acquire low dimensional representation of high dimensional data. I have a strong interest in cardiac remodelling (adaptation of the heart to its environment or a disease), notably the study of the deformation and shape aspects.