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ORCIDAxel Saalbach
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2020 – today
- 2023
[c30]Hrishikesh Deshpande, Axel Saalbach, Tim Harder, Edna Coetser, Shlomo Gotman, Thomas Bülow, Christian Wülker:
Estimation of incomplete organ-coverage using 3D fully convolutional networks. Image Processing 2023- [i10]Francesca Boccardi, Axel Saalbach, Heinrich Schulz, Samuele Salti, Ilyas Sirazitdinov:
Bottom-Up Instance Segmentation of Catheters for Chest X-Rays. CoRR abs/2312.03368 (2023) - 2022
- [j6]Ilyas Sirazitdinov, Heinrich Schulz, Axel Saalbach, Steffen Renisch, Dmitry V. Dylov
:
Tubular shape aware data generation for segmentation in medical imaging. Int. J. Comput. Assist. Radiol. Surg. 17(6): 1091-1099 (2022) - [j5]Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz, Axel Saalbach, Bert Arnrich:
Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data. Sensors 22(14): 5195 (2022) - [c29]Ilyas Sirazitdinov, Axel Saalbach, Heinrich Schulz, Dmitry V. Dylov:
Bi-directional Encoding for Explicit Centerline Segmentation by Fully-Convolutional Networks. MICCAI (4) 2022: 693-703 - [i9]Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz, Axel Saalbach, Bert Arnrich:
Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Data. CoRR abs/2205.03168 (2022) - 2021
- [c28]Ilyas Sirazitdinov, Matthias Lenga, Ivo M. Baltruschat, Dmitry V. Dylov, Axel Saalbach:
Landmark Constellation Models For Central Venous Catheter Malposition Detection. ISBI 2021: 1132-1136 - [c27]Hrishikesh Deshpande, Axel Saalbach, Tim Harder, Stewart Young, Thomas Bülow:
Deep learning for the detection of landmarks in head CT images and automatic quality assessment. Image Processing 2021 - 2020
- [c26]Hrishikesh Deshpande, Tim Harder, Axel Saalbach, Abhivyakti Sawarkar, Thomas Bülow:
Detection Of Foreign Objects In Chest Radiographs Using Deep Learning. ISBI Workshops 2020: 1-4 - [c25]Hrishikesh Deshpande, Martin Bergtholdt, Shlomo Gotman, Axel Saalbach, Julien Sénégas:
Deep Learning Based Segmentation of Body Parts in CT Localizers and Application to Scan Planning. ISBI 2020: 1130-1133 - [c24]Evan Schwab, André Gooßen, Hrishikesh Deshpande, Axel Saalbach:
Localization of Critical Findings in Chest X-Ray Without Local Annotations Using Multi-Instance Learning. ISBI 2020: 1879-1882 - [c23]Matthias Lenga, Heinrich Schulz, Axel Saalbach:
Continual Learning for Domain Adaptation in Chest X-ray Classification. MIDL 2020: 413-423 - [i8]Matthias Lenga, Heinrich Schulz, Axel Saalbach:
Continual Learning for Domain Adaptation in Chest X-ray Classification. CoRR abs/2001.05922 (2020) - [i7]Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch, Axel Saalbach, Michael Grass, Gerhard Adam, Harald Ittrich, Tobias Knopp:
Intelligent Chest X-ray Worklist Prioritization by CNNs: A Clinical Workflow Simulation. CoRR abs/2001.08625 (2020) - [i6]Evan Schwab, André Gooßen, Hrishikesh Deshpande, Axel Saalbach:
Localization of Critical Findings in Chest X-Ray without Local Annotations Using Multi-Instance Learning. CoRR abs/2001.08817 (2020) - [i5]Ilyas Sirazitdinov, Heinrich Schulz, Axel Saalbach, Steffen Renisch, Dmitry V. Dylov:
Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging. CoRR abs/2010.00907 (2020)
2010 – 2019
- 2019
- [c22]Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp:
Abstract: Does Bone Suppression and Lung Detection Improve Chest Disease Classification? Bildverarbeitung für die Medizin 2019: 184 - [c21]Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp:
When Does Bone Suppression And Lung Field Segmentation Improve Chest X-Ray Disease Classification? ISBI 2019: 1362-1366 - [i4]André Gooßen, Hrishikesh Deshpande, Tim Harder, Evan Schwab, Ivo M. Baltruschat, Thusitha De Silva Mabotuwana, Nathan M. Cross, Axel Saalbach:
Deep Learning for Pneumothorax Detection and Localization in Chest Radiographs. CoRR abs/1907.07324 (2019) - 2018
- [c20]Julien Sénégas, Axel Saalbach, Martin Bergtholdt, Sascha Jockel, Detlef Mentrup, Roman Fischbach:
Evaluation of Collimation Prediction Based on Depth Images and Automated Landmark Detection for Routine Clinical Chest X-Ray Exams. MICCAI (2) 2018: 571-579 - [c19]Tom Brosch, Axel Saalbach:
Foveal fully convolutional nets for multi-organ segmentation. Image Processing 2018: 105740U - [c18]Ivo M. Baltruschat, Axel Saalbach, Mattias P. Heinrich, Hannes Nickisch, Sascha Jockel:
Orientation regression in hand radiographs: a transfer learning approach. Image Processing 2018: 105741W - [i3]Ivo M. Baltruschat, Hannes Nickisch, Michael Grass, Tobias Knopp, Axel Saalbach:
Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification. CoRR abs/1803.02315 (2018) - [i2]Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp:
When does Bone Suppression and Lung Field Segmentation Improve Chest X-Ray Disease Classification? CoRR abs/1810.07500 (2018) - 2016
- [j4]Jens von Berg, Stewart Young, Heike Carolus, Robin Wolz, Axel Saalbach, Alberto Hidalgo, Ana Giménez, Tomás Franquet:
A novel bone suppression method that improves lung nodule detection. Int. J. Comput. Assist. Radiol. Surg. 11(4): 641-655 (2016) - [c17]Jens von Berg, Claire Levrier, Heike Carolus, Stewart Young, Axel Saalbach, Patrick Laurent, Raoul Florent:
Decomposing the bony thorax in X-ray images. ISBI 2016: 1068-1071 - 2015
- [c16]Axel Saalbach, Martin Bergtholdt, Thomas Netsch, Julien Sénégas:
Automated anatomy detection in CT localizer images. ISBI 2015: 1151-1154 - [i1]Vlado Menkovski, Zharko Aleksovski, Axel Saalbach, Hannes Nickisch:
Can Pretrained Neural Networks Detect Anatomy? CoRR abs/1512.05986 (2015) - 2014
- [c15]Axel Saalbach, Irina Wächter-Stehle, Cristian Lorenz, Jürgen Weese:
Failure analysis for model-based organ segmentation using outlier detection. Image Processing 2014: 903408 - 2012
- [c14]Dominik Kutra, Axel Saalbach, Helko Lehmann, Alexandra Groth, Sebastian P. M. Dries, Martin W. Krueger, Olaf Dössel, Jürgen Weese:
Automatic Multi-model-Based Segmentation of the Left Atrium in Cardiac MRI Scans. MICCAI (2) 2012: 1-8 - [c13]Dirk Schäfer, Carsten Meyer, Roland Bullens, Axel Saalbach, Peter Eshuis:
Limited Angle C-Arm Tomography and Segmentation for Guidance of Atrial Fibrillation Ablation Procedures. MICCAI (1) 2012: 634-641 - 2011
- [c12]Axel Saalbach, Irina Wächter-Stehle, Reinhard Kneser, Sabine Mollus, Jochen Peters, Jürgen Weese:
Optimizing GHT-Based Heart Localization in an Automatic Segmentation Chain. MICCAI (3) 2011: 463-470 - 2010
- [c11]Thomas Bülow, Axel Saalbach, Martin Bergtholdt, Rafael Wiemker, Hans Buurman, Lina Arbash Meinel, Gillian Newstead:
Heterogeneity of kinetic curve parameters as indicator for the malignancy of breast lesions in DCE MRI. Computer-Aided Diagnosis 2010: 76241H - [c10]Rafael Wiemker, Ekta Dharaiya, Amnon Steinberg, Thomas Bülow, Axel Saalbach, Torbjørn Vik:
Filter learning and evaluation of the computer aided visualization and analysis (CAVA) paradigm for pulmonary nodules using the LIDC-IDRI database. Computer-Aided Diagnosis 2010: 76242U
2000 – 2009
- 2009
- [j3]Axel Saalbach, Oliver Lange, Tim W. Nattkemper, Anke Meyer-Baese:
On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data. Biomed. Signal Process. Control. 4(3): 247-253 (2009) - 2007
- [j2]Anke Meyer-Bäse, Axel Saalbach, Oliver Lange, Axel Wismüller:
Unsupervised clustering of fMRI and MRI time series. Biomed. Signal Process. Control. 2(4): 295-310 (2007) - [c9]Anke Meyer-Bäse, Axel Saalbach:
Graphical Model-Based ICA Applied to the Analysis of fMRI and MRI Time Series. IJCNN 2007: 1651-1656 - 2006
- [b1]Axel Saalbach:
Exploratory analysis of multivariate image data. Bielefeld University, 2006, ISBN 978-3-86727-981-9, pp. 1-186 - 2005
- [j1]Axel Saalbach, Jörg Ontrup, Helge J. Ritter, Tim W. Nattkemper:
Image fusion based on topographic mappings using the hyperbolic space. Inf. Vis. 4(3): 266-275 (2005) - [c8]Axel Saalbach, Thorsten Twellmann, Tim W. Nattkemper, Axel Wismüller, Jörg Ontrup, Helge J. Ritter:
A Hyperbolic Topographic Mapping for Proximity Data. Artificial Intelligence and Applications 2005: 106-111 - [c7]Thorsten Twellmann, Oliver Lichte, Axel Saalbach, Axel Wismüller, Tim W. Nattkemper:
An Adaptive Extended Colour Scale for Comparison of Pseudo Colouring Techniques for DCE-MRI Data. Bildverarbeitung für die Medizin 2005: 312-316 - 2004
- [c6]Gunther Heidemann, Holger Bekel, Ingo Bax, Axel Saalbach:
Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets. ICPR (4) 2004: 487-490 - [c5]Axel Saalbach, Thorsten Twellmann, Tim W. Nattkemper, Mark White, Michael Khazen, Martin O. Leach:
Visualization of multivariate image data using image fusion and perceptually optimized color scales based on sRGB. Image-Guided Procedures 2004 - [c4]Andreas Degenhard, Marc Mutz, Tim W. Nattkemper, Axel Saalbach, Thorsten Twellmann, Mark J. White, Michael Khazen, Linda Pointon, Martin O. Leach:
Multiscale entropy analysis in dynamic contrast-enhanced MRI. Image Processing 2004 - 2003
- [c3]Gunther Heidemann, Axel Saalbach, Helge J. Ritter:
Semi-automatic acquisition and labelling of image data using SOMs. ESANN 2003: 503-508 - 2002
- [c2]Axel Saalbach, Gunther Heidemann, Helge J. Ritter:
Parametrized SOMs for Object Recognition and Pose Estimation. ICANN 2002: 902-907 - [c1]Axel Saalbach, Gunther Heidemann, Helge J. Ritter:
Representing Object Manifolds by Parametrized SOMs. ICPR (2) 2002: 184-187
Coauthor Index
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