Andreas Husch

Orcid: 0000-0001-9404-5127

Affiliations:
  • University of Luxembourg


According to our database1, Andreas Husch authored at least 15 papers between 2015 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Unified Retrieval for Streamlining Biomedical Image Dataset Aggregation and Standardization.
Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023
Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks.
NeuroImage, March, 2023

2022
Rapid artificial intelligence solutions in a pandemic - The COVID-19-20 Lung CT Lesion Segmentation Challenge.
Medical Image Anal., 2022

The effect of dataset confounding on predictions of deep neural networks for medical imaging.
Proceedings of the 2022 Northern Lights Deep Learning Workshop, 2022

Abstract: The Importance of Dataset Choice Lessons Learned from COVID-19 X-ray Imaging Models.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

Initialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation Using Imaging Data.
Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021
Public Covid-19 X-ray datasets and their impact on model bias - A systematic review of a significant problem.
Medical Image Anal., 2021

Automated Deep Learning-based Segmentation of Brain, SEEG and DBS Electrodes on CT Images.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020
FastField: An open-source toolbox for efficient approximation of deep brain stimulation electric fields.
NeuroImage, 2020

On the Composition and Limitations of Publicly Available COVID-19 X-Ray Imaging Datasets.
CoRR, 2020

2019
Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.
NeuroImage, 2019

2017
Integration of sparse electrophysiological measurements with preoperative MRI using 3D surface estimation in deep brain stimulation surgery.
Proceedings of the Medical Imaging 2017: Image-Guided Procedures, 2017

2016
Fast correspondences for statistical shape models of brain structures.
Proceedings of the Medical Imaging 2016: Image Processing, 2016

2015
A solution for multi-alignment by transformation synchronisation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Assessment of Electrode Displacement and Deformation with Respect to Pre-Operative Planning in Deep Brain Stimulation.
Proceedings of the Bildverarbeitung für die Medizin 2015, Algorithmen - Systeme, 2015


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