9 papers
A New Angle on Bones: Robust Pose Estimation in X-Ray and Ultrasound
Ron Keuth, Christoph Großbröhmer, Franziska Halm +5
Measuring the angle between bone structures is a routine task in medical image analysis and provides a key quantitative parameter for diagnosis and treatment planning. Automated me…
Effective Feature Learning for 3D Medical Registration via Domain-Specialized DINO Pretraining
Eytan Kats, Mattias P. Heinrich
Medical image registration is a critical component of clinical imaging workflows, enabling accurate longitudinal assessment, multi-modal data fusion, and image-guided interventions…
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…
Fracture Morphology Classification: Local Multiclass Modeling for Multilabel Complexity
Cassandra Krause, Mattias P. Heinrich, Ron Keuth
Between and of children experience a fracture during their growth years, making accurate diagnosis essential. Fracture morphology, alongside location and fragment…
Shaken or Stirred? An Analysis of MetaFormer's Token Mixing for Medical Imaging
Ron Keuth, Paul Kaftan, Mattias P. Heinrich
The generalization of the Transformer architecture via MetaFormer has reshaped our understanding of its success in computer vision. By replacing self-attention with simpler token m…
A Systematic Analysis of Input Modalities for Fracture Classification of the Paediatric Wrist
Ron Keuth, Maren Balks, Sebastian Tschauner +2
Fractures, particularly in the distal forearm, are among the most common injuries in children and adolescents, with approximately 800 000 cases treated annually in Germany. The AO/…
SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation
Ron Keuth, Lasse Hansen, Maren Balks +4
Semantic segmentation is a crucial task in medical imaging. Although supervised learning techniques have proven to be effective in performing this task, they heavily depend on larg…
DenseSeg: Joint Learning for Semantic Segmentation and Landmark Detection Using Dense Image-to-Shape Representation
Ron Keuth, Lasse Hansen, Maren Balks +4
Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning…
Combining Image- and Geometric-based Deep Learning for Shape Regression: A Comparison to Pixel-level Methods for Segmentation in Chest X-Ray
Ron Keuth, Mattias Heinrich
When solving a segmentation task, shaped-base methods can be beneficial compared to pixelwise classification due to geometric understanding of the target object as shape, preventin…