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Rainer Stiefelhagen
Director Computer Vision for Human-Computer Interaction Lab
Karlsruhe Institute of Technology
Latest
Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging
Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset
Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?
Taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images
Anatomy-Guided Pathology Segmentation
Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy
Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods
Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Images
Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines
Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling
The autoPET challenge: Towards fully automated lesion segmentation in oncologic PET/CT imaging
Mirror U-Net: Marrying Multimodal Fission with Multi-task Learning for Semantic Segmentation in Medical Imaging
Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images based on Physiological and Anatomical Cues
Detailed Annotations of Chest X-Rays via CT Projection for Report Understanding
AutoPET Challenge: Combining nn-Unet with Swin UNETR Augmented by Maximum Intensity Projection Classifier
Jointly Optimized Deep Neural Networks to Synthesize Monoenergetic Images from Single-Energy CT Angiography for Improving Classification of Pulmonary Embolism
Breaking with Fixed Set Pathology Recognition Through Report-Guided Contrastive Training
Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation
CT Angiography Clot Burden Score from Data Mining of Structured Reports for Pulmonary Embolism
Prediction of low-keV monochromatic images from polyenergetic CT scans for improved automatic detection of pulmonary embolism
Self-Guided Multiple Instance Learning for Weakly Supervised Thoracic DiseaseClassification and Localizationin Chest Radiographs
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