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Shallow fully-connected neural networks for ischemic stroke-lesion segmentation in MRI
In: (eds.), Bildverarbeitung in der Medizin 2017, Heidelberg, Informatik aktuell, Springer Vieweg, Berlin Heidelberg, 261-266, 2017
Segmentierung von ischämischen Schlaganfall-Läsionen in multispektralen MR-Bildern mit Random Decision Forests
In: (eds.), Bildverarbeitung für die Medizin 2014, Aachen, Informatik aktuell, Springer, Berlin Heidelberg, 156-161, 2014
Random Forests with Selected Features for Stroke Lesion Segmentation
In: MICCAI Challenge on Ischemic Stroke Lesion Segmentation, ISLES 2015, 18th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, München, 17-22, 2015
Multi-modal Multi-Atlas Segmentation using Discrete Optimisation and Self-Similarities
In: VISCERAL Anatomy3 Segmentation Challenge co-located with IEEE International Symposium on Biomedical Imaging - ISBI 2015, Procceedings, VISCERAL@ISBI 2015, CEUR-WS.org, 2015

MS lesion segmentation in MRI with random forests
Proc. 2015 Longitudinal Multiple Sclerosis Lesion Segmentation Challenge, 1-2, 2015
Longitudinal multiple sclerosis lesion segmentation: Resource and challenge
NeuroImage, 148, 77-102, 2017
Local Problem Forests: Classifier Training for Locally Limited Sub-Problems Using Spectral Clustering
In: 2015 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2015, New York, IEEE Proceedings, The Printing House, 806-809, 2015
ISLES 2016 and 2017-Benchmarking Ischemic Stroke Lesion Outcome Prediction Based on Multispectral MRI
Frontiers in Neurology, 9, 679, 2018
ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
Medical Image Analysis, 35, 250-269, 2017

Ischemic Stroke Lesion Segmentation in Multi-Spectral MR Images with Support Vector Machine Classifiers
In: (eds.), SPIE Medical Imaging 2014: Computer-Aided Diagnosis, San Diego, California, USA, SPIE, 9035, 903504-903504-12, 2014
Ischemic Stroke Lesion Segmentation - Setup of a Challenge
In: (eds.), Student Conference 2015, Medical Engineering Science, Lübeck, 219-222, 2015
Image processing of pulmonary radiography of pediatric patients to assess tuberculosis or pneumonia for the application in diagnosis in low- and middle-income countries
In: (eds.), Student Conference 2016, Medical Engineering Science and Medical Informatics, Lübeck, Infinite Science Publishing, 199-202, 2016
Image Features for Brain Lesion Segmentation Using Random Forests
In: (eds.), Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (Brainles 2015), München, Lecture Notes in Computer Science, Springer International Publishing, 9556, 119-130, 2016
Extra Tree forests for sub-acute ischemic stroke lesion segmentation in MR sequences
Journal of Neuroscience Methods, 240, 89-100, 2015

Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis
Scientific Reports, 10, 1, 1-19, 2020
Enabling on-Demand Features for Decision Forests - An Approach to Lesion Segmentation in MR Volumes
In: (eds.), Student Conference 2015, Medical Engineering Science, Lübeck, 215-218, 2015
Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study
PLOS ONE, 10, 12, e0145118, 2015
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, First International Workshop, Brainles 2015, Held in Conjuction with MICCAI 2015, Springer International Publishing, München, 2016
Automatische Detektion von Okklusionen zerebraler Arterien in 3D-Magnetresonanzangiographiedaten
In: (eds.), Bildverarbeitung für die Medizin 2015, Lübeck, Informatik aktuell, Springer, Berlin Heidelberg, 17-22, 2015