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Books and Theses
- 2021
[b1]Annika Hänsch:
Implications of Dataset Heterogeneity on Deep Learning Performance in Medical Image Segmentation. Jacobs University Bremen, Germany, 2021
Journal Articles
- 2024
- [j2]Alessa Hering
, Max Westphal, Annika Gerken, Haidara Almansour, Michael Maurer, Benjamin P. Geisler, Temke Kohlbrandt, Thomas Eigentler, Teresa Amaral, Nikolas Lessmann, Sergios Gatidis, Horst K. Hahn, Konstantin Nikolaou, Ahmed E. Othman, Jan Hendrik Moltz, Felix Peisen:
Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow. Int. J. Comput. Assist. Radiol. Surg. 19(9): 1689-1697 (2024) - 2022
- [j1]Jürgen Konradi, Milla Zajber, Ulrich Betz, Philipp Drees, Annika Gerken, Hans Meine:
AI-Based Detection of Aspiration for Video-Endoscopy with Visual Aids in Meaningful Frames to Interpret the Model Outcome. Sensors 22(23): 9468 (2022)
Conference and Workshop Papers
- 2023
- [c12]Annika Gerken, Grzegorz Chlebus, Hans Meine, Felix Thielke, Farina Kock, Tobias Paulus, Nasreddin Abolmaali, Andrea Schenk:
Abstract: Liver Tumor Segmentation in Late-phase MRI using Multi-model Training and an Anisotropic U-Net. Bildverarbeitung für die Medizin 2023: 18 - [c11]Ani Ambroladze, Horst K. Hahn, Heba Amer, Michael Ingrisch, Annika Gerken, Markus T. Wenzel, Michael Püsken, Andreas Mittermeier, Christoph Engel, Rita Schmutzler, Eva M. Fallenberg:
CNN-based Whole Breast Segmentation in Longitudinal High-risk MRI Study - Initial Findings on Quality vs. Quantity of Training Annotations. Bildverarbeitung für die Medizin 2023: 159-164 - [c10]Felix Thielke, Farina Kock, Annika Hänsch, Nasreddin Abolmaali, Andrea Schenk, Hans Meine:
Combining arterial and venous CT scans in a multi-encoder network for improved hepatic vessel segmentation. Image Processing 2023 - 2022
- [c9]Annika Hänsch, Felix Thielke, Hans Meine, Shereen Rennebaum, Matthias F. Froelich, Lena S. Becker, Jan B. Hinrichs, Andrea Schenk:
Robust Liver Segmentation with Deep Learning Across DCE-MRI Contrast Phases. Bildverarbeitung für die Medizin 2022: 13-18 - [c8]Luca Canalini, Jan Klein, Annika Gerken, Stefan Heldmann, Alessa Hering, Horst K. Hahn:
Iterative Method to Register Longitudinal MRI Acquisitions in Neurosurgical Context. BrainLes@MICCAI 2022: 262-272 - [c7]Annika Hänsch, Jürgen W. Jenne, Neeraj Upadhyay, Carsten Schmeel, Veronika Purrer, Ullrich Wüllner, Jan Klein:
Deep learning-assisted fully automatic fiber tracking for tremor treatment. Image-Guided Procedures 2022 - [c6]Felix Thielke, Farina Kock, Annika Hänsch, Joachim Georgii, Nasreddin Abolmaali, Itaru Endo, Hans Meine, Andrea Schenk:
Improving deep learning based liver vessel segmentation using automated connectivity analysis. Image Processing 2022 - 2020
- [c5]Jan Hendrik Moltz, Annika Hänsch, Bianca Lassen-Schmidt, Benjamin Haas, A. Genghi, J. Schreier, Tomasz Morgas, Jan Klein:
Learning a Loss Function for Segmentation: A Feasibility Study. ISBI 2020: 357-360 - 2019
- [c4]Annika Hänsch, Volker Dicken, Jan Klein, Tomasz Morgas, Benjamin Haas, Horst K. Hahn:
Artifact-driven sampling schemes for robust female pelvis CBCT segmentation using deep learning. Computer-Aided Diagnosis 2019: 109500T - [c3]Annika Hänsch, Bastian Cheng, Benedikt Frey, Carola Mayer, Marvin Petersen, Iris Lettow, Farhad Yazdan Shenas, Götz Thomalla, Jan Klein, Horst K. Hahn:
Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation. OR/MLCN@MICCAI 2019: 86-94 - [c2]Volker Dicken, Annika Hänsch, Jan Hendrik Moltz, Benjamin Haas, Thomas Coradi, Tomasz Morgas, Jan Klein:
Quantitative and qualitative methods for efficient evaluation of multiple 3D organ segmentations. Image Processing 2019: 1094914 - 2018
- [c1]Annika Hänsch, Michael Schwier, Tobias Gass, Tomasz Morgas, Benjamin Haas, Jan Klein, Horst K. Hahn:
Comparison of different deep learning approaches for parotid gland segmentation from CT images. Computer-Aided Diagnosis 2018: 1057519
Coauthor Index
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