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Lars Heiliger

Results from the autoPET challenge on fully automated lesion segmentation in oncologic PET/CT imaging
ReXamine-Global: A Framework for Uncovering Inconsistencies in Radiology Report Generation Metrics
The autoPET challenge: Towards fully automated lesion segmentation in oncologic PET/CT imaging
Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images based on Physiological and Anatomical Cues
On the Impact of Cross-Domain Data on German Language Models
AutoPET Challenge: Combining nn-Unet with Swin UNETR Augmented by Maximum Intensity Projection Classifier
Beyond Medical Imaging-A Review of Multimodal Deep Learning in Radiology

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