Axel Saalbach

According to our database, Axel Saalbach authored at least 43 papers between 2002 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Bottom-Up Instance Segmentation of Catheters for Chest X-Rays.

Francesca Boccardi, Axel Saalbach, Heinrich Schulz, Samuele Salti, Ilyas Sirazitdinov

CoRR, 2023

Estimation of incomplete organ-coverage using 3D fully convolutional networks.

Hrishikesh Deshpande, Axel Saalbach, Tim Harder, Edna Coetser, Shlomo Gotman, Thomas Bülow, Christian Wülker

Proceedings of the Medical Imaging 2023: Image Processing, 2023

2022

Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data.

Joceline Ziegler, Bjarne Pfitzner, Heinrich Schulz, Axel Saalbach, Bert Arnrich

Sensors, 2022

Tubular shape aware data generation for segmentation in medical imaging.

Ilyas Sirazitdinov, Heinrich Schulz, Axel Saalbach, Steffen Renisch, Dmitry V. Dylov

Int. J. Comput. Assist. Radiol. Surg., 2022

Bi-directional Encoding for Explicit Centerline Segmentation by Fully-Convolutional Networks.

Ilyas Sirazitdinov, Axel Saalbach, Heinrich Schulz, Dmitry V. Dylov

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

2021

Deep learning for the detection of landmarks in head CT images and automatic quality assessment.

Hrishikesh Deshpande, Axel Saalbach, Tim Harder, Stewart Young, Thomas Bülow

Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021

Landmark Constellation Models For Central Venous Catheter Malposition Detection.

Ilyas Sirazitdinov, Matthias Lenga, Ivo M. Baltruschat, Dmitry V. Dylov, Axel Saalbach

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2020

Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging.

Ilyas Sirazitdinov, Heinrich Schulz, Axel Saalbach, Steffen Renisch, Dmitry V. Dylov

CoRR, 2020

Intelligent Chest X-ray Worklist Prioritization by CNNs: A Clinical Workflow Simulation.

Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch, Axel Saalbach, Michael Grass, Gerhard Adam, Harald Ittrich, Tobias Knopp

CoRR, 2020

Continual Learning for Domain Adaptation in Chest X-ray Classification.

Matthias Lenga, Heinrich Schulz, Axel Saalbach

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Localization of Critical Findings in Chest X-Ray Without Local Annotations Using Multi-Instance Learning.

Evan Schwab, André Gooßen, Hrishikesh Deshpande, Axel Saalbach

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Detection Of Foreign Objects In Chest Radiographs Using Deep Learning.

Hrishikesh Deshpande, Tim Harder, Axel Saalbach, Abhivyakti Sawarkar, Thomas Bülow

Proceedings of the 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops), 2020

Deep Learning Based Segmentation of Body Parts in CT Localizers and Application to Scan Planning.

Hrishikesh Deshpande, Martin Bergtholdt, Shlomo Gotman, Axel Saalbach, Julien Sénégas

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019

Deep Learning for Pneumothorax Detection and Localization in Chest Radiographs.

André Gooßen, Hrishikesh Deshpande, Tim Harder, Evan Schwab, Ivo M. Baltruschat, Thusitha De Silva Mabotuwana, Nathan M. Cross, Axel Saalbach

CoRR, 2019

When Does Bone Suppression And Lung Field Segmentation Improve Chest X-Ray Disease Classification?

Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Abstract: Does Bone Suppression and Lung Detection Improve Chest Disease Classification?

Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp

Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.

Ivo M. Baltruschat, Hannes Nickisch, Michael Grass, Tobias Knopp, Axel Saalbach

CoRR, 2018

Foveal fully convolutional nets for multi-organ segmentation.

Tom Brosch, Axel Saalbach

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Orientation regression in hand radiographs: a transfer learning approach.

Ivo M. Baltruschat, Axel Saalbach, Mattias P. Heinrich, Hannes Nickisch, Sascha Jockel

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Evaluation of Collimation Prediction Based on Depth Images and Automated Landmark Detection for Routine Clinical Chest X-Ray Exams.

Julien Sénégas, Axel Saalbach, Martin Bergtholdt, Sascha Jockel, Detlef Mentrup, Roman Fischbach

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2016

A novel bone suppression method that improves lung nodule detection.

Jens von Berg, Stewart Young, Heike Carolus, Robin Wolz, Axel Saalbach, Alberto Hidalgo, Ana Giménez, Tomás Franquet

Int. J. Comput. Assist. Radiol. Surg., 2016

Decomposing the bony thorax in X-ray images.

Jens von Berg, Claire Levrier, Heike Carolus, Stewart Young, Axel Saalbach, Patrick Laurent, Raoul Florent

Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

2015

Can Pretrained Neural Networks Detect Anatomy?

Vlado Menkovski, Zharko Aleksovski, Axel Saalbach, Hannes Nickisch

CoRR, 2015

Automated anatomy detection in CT localizer images.

Axel Saalbach, Martin Bergtholdt, Thomas Netsch, Julien Sénégas

Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

2014

Failure analysis for model-based organ segmentation using outlier detection.

Axel Saalbach, Irina Wächter-Stehle, Cristian Lorenz, Jürgen Weese

Proceedings of the Medical Imaging 2014: Image Processing, 2014

2012

Limited Angle C-Arm Tomography and Segmentation for Guidance of Atrial Fibrillation Ablation Procedures.

Dirk Schäfer, Carsten Meyer, Roland Bullens, Axel Saalbach, Peter Eshuis

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Automatic Multi-model-Based Segmentation of the Left Atrium in Cardiac MRI Scans.

Dominik Kutra, Axel Saalbach, Helko Lehmann, Alexandra Groth, Sebastian P. M. Dries, Martin W. Krueger, Olaf Dössel, Jürgen Weese

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

2011

Optimizing GHT-Based Heart Localization in an Automatic Segmentation Chain.

Axel Saalbach, Irina Wächter-Stehle, Reinhard Kneser, Sabine Mollus, Jochen Peters, Jürgen Weese

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

2010

Filter learning and evaluation of the computer aided visualization and analysis (CAVA) paradigm for pulmonary nodules using the LIDC-IDRI database.

Rafael Wiemker, Ekta Dharaiya, Amnon Steinberg, Thomas Bülow, Axel Saalbach, Torbjørn Vik

Proceedings of the Medical Imaging 2010: Computer-Aided Diagnosis, San Diego, 2010

Heterogeneity of kinetic curve parameters as indicator for the malignancy of breast lesions in DCE MRI.

Thomas Bülow, Axel Saalbach, Martin Bergtholdt, Rafael Wiemker, Hans Buurman, Lina Arbash Meinel, Gillian Newstead

Proceedings of the Medical Imaging 2010: Computer-Aided Diagnosis, San Diego, 2010

2009

On the application of (topographic) independent and tree-dependent component analysis for the examination of DCE-MRI data.

Axel Saalbach, Oliver Lange, Tim W. Nattkemper, Anke Meyer-Baese

Biomed. Signal Process. Control., 2009

2007

Unsupervised clustering of fMRI and MRI time series.

Anke Meyer-Bäse, Axel Saalbach, Oliver Lange, Axel Wismüller

Biomed. Signal Process. Control., 2007

Graphical Model-Based ICA Applied to the Analysis of fMRI and MRI Time Series.

Anke Meyer-Bäse, Axel Saalbach

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Exploratory analysis of multivariate image data.

Axel Saalbach

PhD thesis, 2006

2005

Image fusion based on topographic mappings using the hyperbolic space.

Axel Saalbach, Jörg Ontrup, Helge J. Ritter, Tim W. Nattkemper

Inf. Vis., 2005

An Adaptive Extended Colour Scale for Comparison of Pseudo Colouring Techniques for DCE-MRI Data.

Thorsten Twellmann, Oliver Lichte, Axel Saalbach, Axel Wismüller, Tim W. Nattkemper

Proceedings of the Bildverarbeitung für die Medizin 2005, Algorithmen - Systeme, 2005

A Hyperbolic Topographic Mapping for Proximity Data.

Axel Saalbach, Thorsten Twellmann, Tim W. Nattkemper, Axel Wismüller, Jörg Ontrup, Helge J. Ritter

Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2005

2004

Multiscale entropy analysis in dynamic contrast-enhanced MRI.

Andreas Degenhard, Marc Mutz, Tim W. Nattkemper, Axel Saalbach, Thorsten Twellmann, Mark J. White, Michael Khazen, Linda Pointon, Martin O. Leach

Proceedings of the Medical Imaging 2004: Image Processing, 2004

Visualization of multivariate image data using image fusion and perceptually optimized color scales based on sRGB.

Axel Saalbach, Thorsten Twellmann, Tim W. Nattkemper, Mark White, Michael Khazen, Martin O. Leach

Proceedings of the Medical Imaging 2004: Visualization, 2004

Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets.

Gunther Heidemann, Holger Bekel, Ingo Bax, Axel Saalbach

Proceedings of the 17th International Conference on Pattern Recognition, 2004

2003

Semi-automatic acquisition and labelling of image data using SOMs.

Gunther Heidemann, Axel Saalbach, Helge J. Ritter

Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003

2002

Representing Object Manifolds by Parametrized SOMs.

Axel Saalbach, Gunther Heidemann, Helge J. Ritter

Proceedings of the 16th International Conference on Pattern Recognition, 2002

Parametrized SOMs for Object Recognition and Pose Estimation.

Axel Saalbach, Gunther Heidemann, Helge J. Ritter

Proceedings of the Artificial Neural Networks, 2002