- 3D vessel segmentation
- Application of Diffusion Models for Medical Imaging
- Confidence segmentation
- Converting weights of 2D Vision Transformer for 3D Image Classification
- Counterfactual Modelling
- Deep Learning for Non-rigid 2D-3D Registration
- Exploring Latest Unsupervised Computer Vision Models for Segmentation
- Image Stitching Using Unsupervised/Semi-Supervised Learning
- Image Superresolution Using Generative Models
- Image to image translation with diffusion models
- Natural Language Explanations for Vision and Vision-Language tasks
- Physics-Inspired Neural Networks
- Recent Trends in Medical Image Segmentation
- Sampling Methods in Diffusion Models
- Self-supervised graph representation learning
- Self-supervised Volume Segmentation
- Sensorless US compounding
- Sound and Music Generative Models
- Structural Continuity in Segmentation
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Aufgabenbericht