Recent Work

Projects

Einige unserer Publikationen zum Thema KI in unseren Forschungsschwerpunkten:

• DynaMight: estimating molecular motions with improved reconstruction from cryo-EM images, J. Schwab et al., Nature Methods 2024

• Lifting-based variational multiclass segmentation algorithm: Design, convergence analysis, and implementation with applications in medical imaging, N. Gruber et al., Journal of Computational and Applied Mathematics 2024

• Sparse2Inverse: Self-supervised inversion of sparse-view CT data, N. Gruber et al., arXiv preprint arXiv:2402.16921, 2024

• Single-Image based unsupervised joint segmentation and denoising, N. Gruber et al., arXiv preprint arXiv:2309.10511, 2023

• A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates, N. Gruber et al., Artificial Intelligence in Medicine, 2022

• Deep Learning Methods for Limited Data Problems in X-Ray Tomography, J. Schwab, Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision, 2023

Für weitere Informationen über unsere Forschung: