| Patched diffusion models for unsupervised anomaly detection in brain mri F Behrendt, D Bhattacharya, J Krüger, R Opfer, A Schlaefer Medical Imaging with Deep Learning, 1019-1032, 2024 | 36 | 2024 |
| Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI M Bengs, F Behrendt, J Krüger, R Opfer, A Schlaefer International journal of computer assisted radiology and surgery 16, 1413-1423, 2021 | 30 | 2021 |
| Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction M Bengs, F Behrendt, MH Laves, J Krüger, R Opfer, A Schlaefer Medical Imaging 2022: Computer-Aided Diagnosis 12033, 305-309, 2022 | 10 | 2022 |
| Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with impured training data F Behrendt, M Bengs, F Rogge, J Krüger, R Opfer, A Schlaefer 2022 IEEE 19th international symposium on biomedical imaging (ISBI), 1-4, 2022 | 9 | 2022 |
| Supervised contrastive learning to classify paranasal anomalies in the maxillary sinus D Bhattacharya, BT Becker, F Behrendt, M Bengs, D Beyersdorff, D Eggert, ... International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 8 | 2022 |
| Capturing inter-slice dependencies of 3D brain MRI-scans for unsupervised anomaly detection F Behrendt, M Bengs, D Bhattacharya, J Krüger, R Opfer, A Schlaefer Medical Imaging with Deep Learning, 2022 | 8 | 2022 |
| Guided reconstruction with conditioned diffusion models for unsupervised anomaly detection in brain mris F Behrendt, D Bhattacharya, R Mieling, L Maack, J Krüger, R Opfer, ... arXiv preprint arXiv:2312.04215, 2023 | 7 | 2023 |
| Learning robust representation for laryngeal cancer classification in vocal folds from narrow band images D Bhattacharya, F Behrendt, A Felicio-Briegel, V Volgger, D Eggert, ... Medical Imaging with Deep Learning, 2022 | 6 | 2022 |
| Multiple instance ensembling for paranasal anomaly classification in the maxillary sinus D Bhattacharya, F Behrendt, BT Becker, D Beyersdorff, E Petersen, ... International Journal of Computer Assisted Radiology and Surgery 19 (2), 223-231, 2024 | 5 | 2024 |
| A systematic approach to deep learning-based nodule detection in chest radiographs F Behrendt, M Bengs, D Bhattacharya, J Krüger, R Opfer, A Schlaefer Scientific reports 13 (1), 10120, 2023 | 5 | 2023 |
| Unsupervised anomaly detection of paranasal anomalies in the maxillary sinus D Bhattacharya, F Behrendt, BT Becker, D Beyersdorff, E Petersen, ... Medical Imaging 2023: Computer-Aided Diagnosis 12465, 291-296, 2023 | 4 | 2023 |
| Nodule detection and generation on chest X-rays: NODE21 Challenge E Sogancioglu, B Van Ginneken, F Behrendt, M Bengs, A Schlaefer, ... IEEE Transactions on Medical Imaging, 2024 | 3 | 2024 |
| Data-efficient vision transformers for multi-label disease classification on chest radiographs F Behrendt, D Bhattacharya, J Krüger, R Opfer, A Schlaefer Current directions in biomedical engineering 8 (1), 34-37, 2022 | 3 | 2022 |
| BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRI R Opfer, J Krüger, T Buddenkotte, L Spies, F Behrendt, S Schippling, ... International Journal of Computer Assisted Radiology and Surgery, 1-9, 2024 | 1 | 2024 |
| Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection F Behrendt, D Bhattacharya, L Maack, J Krüger, R Opfer, R Mieling, ... arXiv preprint arXiv:2403.14262, 2024 | 1 | 2024 |
| PolypNextLSTM: A lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM D Bhattacharya, K Reuter, F Behrendt, L Maack, S Grube, A Schlaefer arXiv preprint arXiv:2402.11585, 2024 | 1 | 2024 |
| Optical coherence elastography needle for biomechanical characterization of deep tissue R Mieling, S Latus, M Fischer, F Behrendt, A Schlaefer International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 1 | 2023 |
| Generalization of spatio-temporal deep learning for vision-based force estimation F Behrendt, N Gessert, A Schlaefer Current directions in biomedical engineering 6 (1), 20200024, 2020 | 1 | 2020 |
| Leveraging the Mahalanobis Distance to Enhance Unsupervised Brain MRI Anomaly Detection F Behrendt, D Bhattacharya, R Mieling, L Maack, J Krüger, R Opfer, ... International Conference on Medical Image Computing and Computer-Assisted …, 2024 | | 2024 |
| Needle tracking in low-resolution ultrasound volumes using deep learning S Grube, S Latus, F Behrendt, O Riabova, M Neidhardt, A Schlaefer International Journal of Computer Assisted Radiology and Surgery, 1-7, 2024 | | 2024 |
Alexander SchlaeferTUHH在 tuhh.de 的电子邮件经过验证
Alexander SchlaeferTUHH在 tuhh.de 的电子邮件经过验证
Debayan BhattacharyaHamburg University of Technology在 tuhh.de 的电子邮件经过验证
Marcel BengsHamburg University of Technology在 tuhh.de 的电子邮件经过验证