Dr. Andreas Husch
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| Faculty or Centre | Luxembourg Centre for Systems Biomedicine | ||||||||
| Department | Interventional Neuroscience | ||||||||
| Postal Address |
Université du Luxembourg 6, avenue du Swing L-4367 Belvaux |
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| Campus Office | BioTech II, 0.08 | ||||||||
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| Telephone | (+352) 46 66 44 9087 | ||||||||
| Fax | (+352) 46 66 44 39087 | ||||||||
Postdoc in the Interventional Neuroscience group (Hertel Lab) and Systems Control group (Goncalves lab)
Last updated on: Thursday, 18 October 2018
2021
Public Covid-19 X-ray datasets and their impact on model bias - a systematic review of a significant problem; ; ;
E-print/Working paper (2021)
Stages of COVID-19 pandemic and paths to herd immunity by vaccination: dynamical model comparing Austria, Luxembourg and Sweden; ; ; ; ; ; ; ; ;
E-print/Working paper (2021)
2020
Impressive weight gain after deep brain stimulation of nucleus accumbens in treatment- resistant bulimic anorexia nervosa; ; ;
in BMJ Case Reports (2020)
FastField: An Open-Source Toolbox for Efficient Approximation of Deep Brain Stimulation Electric Fields; ; ; ;
in NeuroImage (2020)
Automatic Detection of Nigrosome Degeneration in Susceptibility-Weighted MRI for Computer-Aided Diagnosis of Parkinson’s Disease Using Machine Learning; ;
in Movement Disorders: Volume 35, Number S1, September 2020 (2020, September 12)
On the Composition and Limitations of Publicly Available COVID-19 X-Ray Imaging Datasets; ; ;
E-print/Working paper (2020)
Assessing suppression strategies against epidemicoutbreaks like COVID-19: the SPQEIR model; ; ; ; ; ; ; ; ;
E-print/Working paper (2020)
2019
From tech to bench: Deep Learning pipeline for image segmentation of high-throughput high-content microscopy data; ; ; ; ; ; ; ; ; ;
Poster (2019, November 29)
Deep Learning Quality Control for High-Throughput High-Content Screening Microscopy Images; ; ; ;
Poster (2019, October 10)
Habenula deep brain stimulation for refractory bipolar disorder.; ; ; ; ; ; ; ; ;
in Brain stimulation (2019)
2018
Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
in NeuroImage (2018)
PaCER - A fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation; ; ; ;
in NeuroImage: Clinical (2018), 17
Post-operative deep brain stimulation assessment: Automatic data integration and report generation; ; ; ; ;
in Brain Stimulation (2018)
Using automated electrode localization to guide stimulation management in DBS; ; ; ; ;
in Annals of Clinical and Translational Neurology (2018), 0(0),
2017
Integration of sparse electrophysiological measurements with preoperative MRI using 3D surface estimation in deep brain stimulation surgery; ; ;
in Webster, Robert; Fei, Baowei (Eds.) Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling (2017, February 14)
2016
Fast Correspondences for Statistical Shape Models of Brain Structures; ; ; ; ; ;
in SPIE Medical Imaging (2016, March)
2015
A solution for Multi-Alignment by Transformation Synchronisation; ; ; ; ;
in The proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)
Transitively Consistent and Unbiased Multi-Image Registration Using Numerically Stable Transformation Synchronisation; ; ; ; ; ;
in MIDAS Journal (2015)
Susceptibility-Weighted MRI for Deep Brain Stimulation: Potentials in Trajectory Planning; ; ; ;
in Stereotactic & Functional Neurosurgery (2015), 93(5), 303-308
Assessment of Electrode Displacement and Deformation with Respect to Pre-Operative Planning in Deep Brain Stimulation; ; ; ;
in Handels, Heinz; Deserno, Thomas Martin; Meinzer, Hans-Peter; Tolxdorff, Thomas (Eds.) Bildverarbeitung für die Medizin 2015 (2015)
2014
An Extensible Development Environment for 3D Segmentations based on Active Shape Models; ; ;
in Shape Symposium (2014)
Improving the Consistency of Manual Deep Brain Structure Segmentations by Combining Variational Interpolation, Simultaneous Multi-Modality Visualisation and Histogram Equilisation; ; ; ; ; ;
in Biomedizinische Technik. Biomedical Engineering (2014), 59(1), 131-134
DTI of the visual pathway - white matter tracts and cerebral lesions.; ; ; ; ; ; ;
in Journal of visualized experiments : JoVE (2014), (90),
