Anders Nymark Christensen

Orcid: 0000-0002-3668-3128

According to our database1, Anders Nymark Christensen authored at least 23 papers between 2016 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Feature-Centered First Order Structure Tensor Scale-Space in 2D and 3D.
CoRR, 2024

Deployment of Deep Learning Model in Real World Clinical Setting: A Case Study in Obstetric Ultrasound.
CoRR, 2024

Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment.
CoRR, 2024

Unsupervised Detection of Fetal Brain Anomalies Using Denoising Diffusion Models.
Proceedings of the Simplifying Medical Ultrasound - 5th International Workshop, 2024

Shortcut Learning in Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Is This Hard for You? Personalized Human Difficulty Estimation for Skin Lesion Diagnosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Learning Semantic Image Quality for Fetal Ultrasound from Noisy Ranking Annotation.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Removing confounding information from fetal ultrasound images.
CoRR, 2023

Multi-modal data generation with a deep metric variational autoencoder.
Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

An Automatic Guidance and Quality Assessment System for Doppler Imaging of Umbilical Artery.
Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023

Leveraging Shape and Spatial Information for Spontaneous Preterm Birth Prediction.
Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023

DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentation.
Proceedings of the Information Processing in Medical Imaging, 2023

2022
A Deep Learning Approach for Detecting Otitis Media From Wideband Tympanometry Measurements.
IEEE J. Biomed. Health Informatics, 2022

Deep Unsupervised 4-D Seismic 3-D Time-Shift Estimation With Convolutional Neural Networks.
IEEE Trans. Geosci. Remote. Sens., 2022

I saw, I conceived, I concluded: Progressive Concepts as Bottlenecks.
CoRR, 2022

DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentation.
CoRR, 2022

Was that so Hard? Estimating Human Classification Difficulty.
Proceedings of the Applications of Medical Artificial Intelligence, 2022

2021
Deep metric learning for otitis media classification.
Medical Image Anal., 2021

Complex-valued neural networks for machine learning on non-stationary physical data.
Comput. Geosci., 2021

Faster Multi-Object Segmentation using Parallel Quadratic Pseudo-Boolean Optimization.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Sparse Layered Graphs for Multi-Object Segmentation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2017
Automatic Segmentation of Abdominal Fat in MRI-Scans, Using Graph-Cuts and Image Derived Energies.
Proceedings of the Image Analysis - 20th Scandinavian Conference, 2017

2016
Data Analysis of Medical Images: CT, MRI, Phase Contrast X-ray and PET.
PhD thesis, 2016


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