Lennart Maack

According to our database, Lennart Maack authored at least 8 papers between 2024 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Tracking Any Point Methods for Markerless 3D Tissue Tracking in Endoscopic Stereo Images.

Konrad Reuter, Suresh Guttikonda, Sarah Latus, Lennart Maack, Christian Betz, Tobias Maurer, Alexander Schlaefer

CoRR, August, 2025

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

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., October, 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., September, 2024

Efficient Anatomy Segmentation in Laparoscopic Surgery using Multi-Teacher Knowledge Distillation.

Lennart Maack, Finn Behrendt, Debayan Bhattacharya, Sarah Latus, Alexander Schlaefer

Proceedings of the Medical Imaging with Deep Learning, 3-5 July 2024, Paris, France., 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

Proceedings of the Medical Imaging with Deep Learning, 3-5 July 2024, Paris, France., 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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

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

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024