7 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…
Multiparameter regularization and aggregation in the context of polynomial functional regression
Elke R. Gizewski, Markus Holzleitner, Lukas Mayer-Suess +2
Most of the recent results in polynomial functional regression have been focused on an in-depth exploration of single-parameter regularization schemes. In contrast, in this study w…
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…
XSRD-Net: EXplainable Stroke Relapse Detection
Christian Gapp, Elias Tappeiner, Martin Welk +8
Stroke is the second most frequent cause of death world wide with an annual mortality of around 5.5 million. Recurrence rates of stroke are between 5 and 25% in the first year. As…