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Finn Behrendt
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2020 – today
- 2024
- [j7]Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer
:
Multiple instance ensembling for paranasal anomaly classification in the maxillary sinus. Int. J. Comput. Assist. Radiol. Surg. 19(2): 223-231 (2024) - [j6]Debayan Bhattacharya
Self-supervised learning for classifying paranasal anomalies in the maxillary sinus. Int. J. Comput. Assist. Radiol. Surg. 19(9): 1713-1721 (2024) - [j5]Roland Opfer
BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRI. Int. J. Comput. Assist. Radiol. Surg. 19(9): 1763-1771 (2024) - [j4]Sarah Grube
Needle tracking in low-resolution ultrasound volumes using deep learning. Int. J. Comput. Assist. Radiol. Surg. 19(10): 1975-1981 (2024) - [j3]Debayan Bhattacharya
PolypNextLSTM: a lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM. Int. J. Comput. Assist. Radiol. Surg. 19(10): 2111-2119 (2024) - [j2]Ecem Sogancioglu
Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge. IEEE Trans. Medical Imaging 43(8): 2839-2853 (2024) - [c11]Finn Behrendt, Debayan Bhattacharya, Lennart Maack, Julia Krüger, Roland Opfer, Robin Mieling, Alexander Schlaefer:
Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection. ISBI 2024: 1-4 - [c10]Robin Mieling, Sarah Latus, Finn Behrendt, Debayan Bhattacharya, Maximilian Neidhardt, Alexander Schlaefer:
Can Complex-Valued Neural Networks Improve Force Sensing with Optical Coherence Tomography? ISBI 2024: 1-4 - [c9]Finn Behrendt
Leveraging the Mahalanobis Distance to Enhance Unsupervised Brain MRI Anomaly Detection. MICCAI (11) 2024: 394-404 - [i14]Ecem Sogancioglu, Bram van Ginneken, Finn Behrendt, Marcel Bengs, Alexander Schlaefer, Miron Radu, Di Xu, Ke Sheng, Fabien Scalzo, Eric Marcus, Samuele Papa, Jonas Teuwen, Ernst Th. Scholten, Steven Schalekamp, Nils Hendrix, Colin Jacobs, Ward Hendrix, Clara I. Sánchez, Keelin Murphy:
Nodule detection and generation on chest X-rays: NODE21 Challenge. CoRR abs/2401.02192 (2024) - [i13]Debayan Bhattacharya, Konrad Reuter, Finn Behrendt, Lennart Maack, Sarah Grube, Alexander Schlaefer:
PolypNextLSTM: A lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM. CoRR abs/2402.11585 (2024) - [i12]Finn Behrendt, Debayan Bhattacharya, Lennart Maack, Julia Krüger, Roland Opfer, Robin Mieling, Alexander Schlaefer:
Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection. CoRR abs/2403.14262 (2024) - [i11]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:
Self-supervised learning for classifying paranasal anomalies in the maxillary sinus. CoRR abs/2404.18599 (2024) - [i10]Finn Behrendt, Debayan Bhattacharya, Robin Mieling, Lennart Maack, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly Detection. CoRR abs/2407.12474 (2024) - 2023
- [c8]Debayan Bhattacharya, Sarah Latus, Finn Behrendt, Florin Thimm, Dennis Eggert, Christian Betz, Alexander Schlaefer:
Tissue Classification During Needle Insertion Using Self-Supervised Contrastive Learning and Optical Coherence Tomography. EMBC 2023: 1-4 - [c7]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Nodule Detection in Chest Radiographs with Unsupervised Pre-Trained Detection Transformers. ISBI 2023: 1-4 - [c6]Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer
Unsupervised anomaly detection of paranasal anomalies in the maxillary sinus. Computer-Aided Diagnosis 2023 - [c5]Robin Mieling
Optical Coherence Elastography Needle for Biomechanical Characterization of Deep Tissue. MICCAI (9) 2023: 607-617 - [c4]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI. MIDL 2023: 1019-1032 - [i9]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI. CoRR abs/2303.03758 (2023) - [i8]Debayan Bhattacharya, Finn Behrendt, Benjamin Tobias Becker, Dirk Beyersdorff, Elina Petersen, Marvin Petersen, Bastian Cheng, Dennis Eggert, Christian Betz, Anna Sophie Hoffmann, Alexander Schlaefer
Multiple Instance Ensembling For Paranasal Anomaly Classification In The Maxillary Sinus. CoRR abs/2303.17915 (2023) - [i7]Debayan Bhattacharya, Sarah Latus, Finn Behrendt, Florin Thimm, Dennis Eggert, Christian Betz, Alexander Schlaefer
Tissue Classification During Needle Insertion Using Self-Supervised Contrastive Learning and Optical Coherence Tomography. CoRR abs/2304.13574 (2023) - [i6]Finn Behrendt, Debayan Bhattacharya, Robin Mieling, Lennart Maack, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs. CoRR abs/2312.04215 (2023) - 2022
- [c3]Finn Behrendt, Marcel Bengs, Frederik Rogge, Julia Krüger, Roland Opfer, Alexander Schlaefer
Unsupervised Anomaly Detection in 3D Brain MRI Using Deep Learning with Impured Training Data. ISBI 2022: 1-4 - [c2]Marcel Bengs, Finn Behrendt, Max-Heinrich Laves, Julia Krüger, Roland Opfer, Alexander Schlaefer
Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction. Computer-Aided Diagnosis 2022 - [c1]Debayan Bhattacharya, Benjamin Tobias Becker, Finn Behrendt, Marcel Bengs, Dirk Beyersdorff, Dennis Eggert, Elina Petersen, Florian Jansen, Marvin Petersen, Bastian Cheng, Christian Betz, Alexander Schlaefer
Supervised Contrastive Learning to Classify Paranasal Anomalies in the Maxillary Sinus. MICCAI (3) 2022: 429-438 - [i5]Marcel Bengs, Finn Behrendt, Max-Heinrich Laves, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with Multi-Task Brain Age Prediction. CoRR abs/2201.13081 (2022) - [i4]Finn Behrendt, Marcel Bengs, Frederik Rogge, Julia Krüger, Roland Opfer, Alexander Schlaefer:
Unsupervised Anomaly Detection in 3D Brain MRI using Deep Learning with impured training data. CoRR abs/2204.05778 (2022) - [i3]Finn Behrendt, Debayan Bhattacharya, Julia Krüger, Roland Opfer, Alexander Schlaefer
Data-Efficient Vision Transformers for Multi-Label Disease Classification on Chest Radiographs. CoRR abs/2208.08166 (2022) - [i2]Debayan Bhattacharya, Benjamin Tobias Becker, Finn Behrendt, Marcel Bengs, Dirk Beyersdorff, Dennis Eggert, Elina Petersen, Florian Jansen, Marvin Petersen, Bastian Cheng, Christian Betz, Alexander Schlaefer, Anna Sophie Hoffmann:
Supervised Contrastive Learning to Classify Paranasal Anomalies in the Maxillary Sinus. CoRR abs/2209.01937 (2022) - 2021
- [j1]Marcel Bengs
Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI. Int. J. Comput. Assist. Radiol. Surg. 16(9): 1413-1423 (2021) - [i1]Marcel Bengs, Finn Behrendt, Julia Krüger, Roland Opfer, Alexander Schlaefer:
3-Dimensional Deep Learning with Spatial Erasing for Unsupervised Anomaly Segmentation in Brain MRI. CoRR abs/2109.06540 (2021)
Coauthor Index
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