Finn Behrendt

Orcid: 0000-0001-7191-6508

According to our database1, Finn Behrendt authored at least 21 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2021
2022
2023
2024
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Needle tracking in low-resolution ultrasound volumes using deep learning.
Int. J. Comput. Assist. Radiol. Surg., October, 2024

PolypNextLSTM: a lightweight and fast polyp video segmentation network using ConvNext and ConvLSTM.
Int. J. Comput. Assist. Radiol. Surg., October, 2024

BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRI.
Int. J. Comput. Assist. Radiol. Surg., September, 2024

Self-supervised learning for classifying paranasal anomalies in the maxillary sinus.
Int. J. Comput. Assist. Radiol. Surg., September, 2024

Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge.
IEEE Trans. Medical Imaging, August, 2024

Multiple instance ensembling for paranasal anomaly classification in the maxillary sinus.
Int. J. Comput. Assist. Radiol. Surg., February, 2024

Leveraging the Mahalanobis Distance to Enhance Unsupervised Brain MRI Anomaly Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Can Complex-Valued Neural Networks Improve Force Sensing with Optical Coherence Tomography?
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs.
CoRR, 2023

Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI.
Proceedings of the Medical Imaging with Deep Learning, 2023

Optical Coherence Elastography Needle for Biomechanical Characterization of Deep Tissue.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Unsupervised anomaly detection of paranasal anomalies in the maxillary sinus.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023

Nodule Detection in Chest Radiographs with Unsupervised Pre-Trained Detection Transformers.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Tissue Classification During Needle Insertion Using Self-Supervised Contrastive Learning and Optical Coherence Tomography.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

2022
Data-Efficient Vision Transformers for Multi-Label Disease Classification on Chest Radiographs.
CoRR, 2022

Supervised Contrastive Learning to Classify Paranasal Anomalies in the Maxillary Sinus.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Unsupervised anomaly detection in 3D brain MRI using deep learning with multi-task brain age prediction.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022

Unsupervised Anomaly Detection in 3D Brain MRI Using Deep Learning with Impured Training Data.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

2021
3-Dimensional Deep Learning with Spatial Erasing for Unsupervised Anomaly Segmentation in Brain MRI.
CoRR, 2021

Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI.
Int. J. Comput. Assist. Radiol. Surg., 2021


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