5 papers
Schrödinger-Inspired Time-Evolution for 4D Deformation Forecasting
Ahsan Raza Siyal, Markus Haltmeier, Ruth Steiger +2
Spatiotemporal forecasting of complex three-dimensional phenomena (4D: 3D + time) is fundamental to applications in medical imaging, fluid and material dynamics, and geophysics. In…
Robust Rigid and Non-Rigid Medical Image Registration Using Learnable Edge Kernels
Ahsan Raza Siyal, Markus Haltmeier, Ruth Steiger +3
Medical image registration is crucial for various clinical and research applications including disease diagnosis or treatment planning which require alignment of images from differ…
DARE: A Deformable Adaptive Regularization Estimator for Learning-Based Medical Image Registration
Ahsan Raza Siyal, Markus Haltmeier, Ruth Steiger +3
Deformable medical image registration is a fundamental task in medical image analysis. While deep learning-based methods have demonstrated superior accuracy and computational effic…
Semi-supervised learning and integration of multi-sequence MR-images for carotid vessel wall and plaque segmentation
Marie-Christine Pali, Christina Schwaiger, Malik Galijasevic +3
The analysis of carotid arteries, particularly plaques, in multi-sequence Magnetic Resonance Imaging (MRI) data is crucial for assessing the risk of atherosclerosis and ischemic st…
What are You Looking at? Modality Contribution in Multimodal Medical Deep Learning
Christian Gapp, Elias Tappeiner, Martin Welk +3
Purpose High dimensional, multimodal data can nowadays be analyzed by huge deep neural networks with little effort. Several fusion methods for bringing together different modalitie…