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Georg Langs

Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University Vienna, Austria

Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI


Aug 09, 2021
Lucas Fidon, Michael Aertsen, Nada Mufti, Thomas Deprest, Doaa Emam, Frédéric Guffens, Ernst Schwartz, Michael Ebner, Daniela Prayer, Gregor Kasprian, Anna L. David, Andrew Melbourne, Sébastien Ourselin, Jan Deprest, Georg Langs, Tom Vercauteren

* Accepted at the MICCAI 2021 Perinatal, Preterm and Paediatric Image Analysis (PIPPI) workshop 

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Continual Active Learning for Efficient Adaptation of Machine Learning Models to Changing Image Acquisition


Jun 07, 2021
Matthias Perkonigg, Johannes Hofmanninger, Georg Langs

* Accepted for publication at the 27th international conference on Information Processing in Medical Imaging (IPMI) 2021 

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The Effects of Skin Lesion Segmentation on the Performance of Dermatoscopic Image Classification


Aug 28, 2020
Amirreza Mahbod, Philipp Tschandl, Georg Langs, Rupert Ecker, Isabella Ellinger

* Accepted to the Computer Methods and Programs in Biomedicine journal 

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Dynamic memory to alleviate catastrophic forgetting in continuous learning settings


Jul 07, 2020
Johannes Hofmanninger, Matthias Perkonigg, James A. Brink, Oleg Pianykh, Christian Herold, Georg Langs

* The first two authors contributed equally. Accepted at MICCAI 2020 

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Separation of target anatomical structure and occlusions in chest radiographs


Feb 03, 2020
Johannes Hofmanninger, Sebastian Roehrich, Helmut Prosch, Georg Langs

* 5 pages, 1 figure 

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Automatic lung segmentation in routine imaging is a data diversity problem, not a methodology problem


Jan 31, 2020
Johannes Hofmanninger, Florian Prayer, Jeanny Pan, Sebastian Rohrich, Helmut Prosch, Georg Langs

* 10 pages, 4 figures, 5 tables 

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Unsupervised deep clustering for predictive texture pattern discovery in medical images


Jan 31, 2020
Matthias Perkonigg, Daniel Sobotka, Ahmed Ba-Ssalamah, Georg Langs

* Medical Imaging meets NeurIPS 2019 

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Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT


May 29, 2019
Philipp Seeböck, José Ignacio Orlando, Thomas Schlegl, Sebastian M. Waldstein, Hrvoje Bogunović, Sophie Klimscha, Georg Langs, Ursula Schmidt-Erfurth

* Accepted for publication in IEEE Transactions on Medical Imaging, 2019 

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Using CycleGANs for effectively reducing image variability across OCT devices and improving retinal fluid segmentation


Jan 25, 2019
Philipp Seeböck, David Romo-Bucheli, Sebastian Waldstein, Hrvoje Bogunović, José Ignacio Orlando, Bianca S. Gerendas, Georg Langs, Ursula Schmidt-Erfurth

* * Contributed equally (order was defined by flipping a coin) --------------- Accepted for publication in the "IEEE International Symposium on Biomedical Imaging (ISBI) 2019" 

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Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data


Oct 31, 2018
Philipp Seeböck, Sebastian M. Waldstein, Sophie Klimscha, Hrvoje Bogunovic, Thomas Schlegl, Bianca S. Gerendas, René Donner, Ursula Schmidt-Erfurth, Georg Langs

* Accepted for publication in IEEE Transactions on Medical Imaging, 2018 

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Keypoint Transfer for Fast Whole-Body Segmentation


Jun 22, 2018
Christian Wachinger, Matthew Toews, Georg Langs, William Wells, Polina Golland

* Accepted for publication at IEEE Transactions on Medical Imaging 

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Fully Automated Segmentation of Hyperreflective Foci in Optical Coherence Tomography Images


May 08, 2018
Thomas Schlegl, Hrvoje Bogunovic, Sophie Klimscha, Philipp Seeböck, Amir Sadeghipour, Bianca Gerendas, Sebastian M. Waldstein, Georg Langs, Ursula Schmidt-Erfurth


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NIPS 2016 Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI 2016)


Apr 10, 2017
Leila Wehbe, Anwar Nunez-Elizalde, Marcel van Gerven, Irina Rish, Brian Murphy, Moritz Grosse-Wentrup, Georg Langs, Guillermo Cecchi


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Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery


Mar 17, 2017
Thomas Schlegl, Philipp Seeböck, Sebastian M. Waldstein, Ursula Schmidt-Erfurth, Georg Langs

* To be published in the proceedings of the international conference on Information Processing in Medical Imaging (IPMI), 2017 

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Identifying and Categorizing Anomalies in Retinal Imaging Data


Dec 02, 2016
Philipp Seeböck, Sebastian Waldstein, Sophie Klimscha, Bianca S. Gerendas, René Donner, Thomas Schlegl, Ursula Schmidt-Erfurth, Georg Langs

* Extended Abstract, Accepted for NIPS 2016 Workshop "Machine Learning for Health" 

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