Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection. - Finn Behrendt; Debayan Bhattacharya; Lennart Maack; Julia Krüger; Roland Opfer; Robin Mieling; Alexander Schlaefer (ISBI, 2024)

Leveraging the Mahalanobis Distance to Enhance Unsupervised Brain MRI Anomaly Detection. - Finn Behrendt; Debayan Bhattacharya; Robin Mieling; Lennart Maack; Julia Krüger; Roland Opfer; Alexander Schlaefer (MICCAI (11), 2024)

Combining Reconstruction-based Unsupervised Anomaly Detection with Supervised Segmentation for Brain MRIs. - Finn Behrendt; Debayan Bhattacharya; Lennart Maack; Julia Krüger; Roland Opfer; Alexander Schlaefer (MIDL, 2024)

Efficient Anatomy Segmentation in Laparoscopic Surgery using Multi-Teacher Knowledge Distillation. - Lennart Maack; Finn Behrendt; Debayan Bhattacharya; Sarah Latus; Alexander Schlaefer (MIDL, 2024)

Self-supervised learning for classifying paranasal anomalies in the maxillary sinus. - Debayan Bhattacharya; Finn Behrendt; Benjamin Tobias Becker; Lennart Maack; Dirk Beyersdorff; Elina Petersen; Marvin Petersen; Bastian Cheng; Dennis Eggert; Christian Betz; Anna Sophie Hoffmann; Alexander Schlaefer (Int. J. Comput. Assist. Radiol. Surg., 2024)

PolypNextLSTM: a lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM. - Debayan Bhattacharya; Konrad Reuter; Finn Behrendt; Lennart Maack; Sarah Grube; Alexander Schlaefer (Int. J. Comput. Assist. Radiol. Surg., 2024)

Guided reconstruction with conditioned diffusion models for unsupervised anomaly detection in brain MRIs. - Finn Behrendt; Debayan Bhattacharya; Robin Mieling; Lennart Maack; Julia Krüger; Roland Opfer; Alexander Schlaefer (Comput. Biol. Medicine, 2025)