1.4k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Radboud University Medical CenterNL11 papers
- Radboud University NijmegenNL11 papers
- RWTH Aachen UniversityDE11 papers
- Charité - Universitätsmedizin BerlinDE7 papers
- University of BremenDE7 papers
- University of LübeckDE7 papers
- German Cancer Research CenterDE6 papers
- Heidelberg UniversityDE6 papers
- Brigham and Women's HospitalUS5 papers
- Harvard UniversityUS5 papers
- University Hospital HeidelbergDE5 papers
- Freie Universität BerlinDE4 papers
16 papers · 1 filter
Depth to Anatomy: Organ Localization from Depth Images for Automated Patient Table Positioning in Radiology Workflow
Eytan Kats, Kai Geissler, Daniel Mensing +4
In clinical radiology, accurate patient table positioning is essential to align specific internal organs of interest with the scanner imaging isocenter, ensuring image quality and…
Robust Renal Mass Segmentation on CT: A Validation Study of an AI-Based Framework
Sarah de Boer, Hartmut Häntze, Kiran Vaidhya Venkadesh +9
Renal mass segmentation has important potential to enhance the clinical workflow, especially in settings requiring quantitative assessments. Kidney volume could serve as an importa…
Carotid Artery Plaque Analysis in 3D Based on Distance Encoding in Mesh Representations
Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter +3
Purpose: Enabling a comprehensive and robust assessment of carotid artery plaques in 3D through extraction and visualization of quantitative plaque parameters. These parameters hav…
Learning Wall Segmentation in 3D Vessel Trees using Sparse Annotations
Hinrich Rahlfs, Markus Hüllebrand, Sebastian Schmitter +3
We propose a novel approach that uses sparse annotations from clinical studies to train a 3D segmentation of the carotid artery wall. We use a centerline annotation to sample perpe…
The NCI Imaging Data Commons as a platform for reproducible research in computational pathology
Daniela P. Schacherer, Markus D. Herrmann, David A. Clunie +7
Background and Objectives: Reproducibility is a major challenge in developing machine learning (ML)-based solutions in computational pathology (CompPath). The NCI Imaging Data Comm…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Comparison of different automatic solutions for resection cavity segmentation in postoperative MRI volumes including longitudinal acquisitions
Luca Canalini, Jan Klein, Nuno Pedrosa de Barros +3
In this work, we compare five deep learning solutions to automatically segment the resection cavity in postoperative MRI. The proposed methods are based on the same 3D U-Net archit…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
mlVIRNET: Multilevel Variational Image Registration Network
Alessa Hering, Bram van Ginneken, Stefan Heldmann
We present a novel multilevel approach for deep learning based image registration. Recently published deep learning based registration methods have shown promising results for a wi…
The Liver Tumor Segmentation Benchmark (LiTS)
Patrick Bilic, Patrick Christ, Hongwei Bran Li +106
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…
Fully-deformable 3D image registration in two seconds
Daniel Budelmann, Lars König, Nils Papenberg +1
We present a highly parallel method for accurate and efficient variational deformable 3D image registration on a consumer-grade graphics processing unit (GPU). We build on recent m…
Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking
Alessa Hering, Sven Kuckertz, Stefan Heldmann +1
While deep learning has achieved significant advances in accuracy for medical image segmentation, its benefits for deformable image registration have so far remained limited to red…
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard
Wouter Bulten, Péter Bándi, Jeffrey Hoven +7
Prostate cancer (PCa) is graded by pathologists by examining the architectural pattern of cancerous epithelial tissue on hematoxylin and eosin (H&E) stained slides. Given the impor…
Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration
Jan Rühaak, Thomas Polzin, Stefan Heldmann +4
We present a novel algorithm for the registration of pulmonary CT scans. Our method is designed for large respiratory motion by integrating sparse keypoint correspondences into a d…
Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions
Nikolas Lessmann, Bram van Ginneken, Majd Zreik +4
Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable qua…
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge
Arnaud Arindra Adiyoso Setio, Alberto Traverso, Thomas de Bel +29
Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few…