57 citations · 101 across the 4 of their papers we have counts for
3 papers · 1 filter
The Segment Anything foundation model achieves favorable brain tumor autosegmentation accuracy on MRI to support radiotherapy treatment planning
Florian Putz, Johanna Grigo, Thomas Weissmann +13
Background: Tumor segmentation in MRI is crucial in radiotherapy (RT) treatment planning for brain tumor patients. Segment anything (SA), a novel promptable foundation model for au…
Deep learning for automatic head and neck lymph node level delineation provides expert-level accuracy
Thomas Weissmann, Yixing Huang, Stefan Fischer +16
Background: Deep learning (DL)-based head and neck lymph node level (HN_LNL) autodelineation is of high relevance to radiotherapy research and clinical treatment planning but still…
Deep learning for brain metastasis detection and segmentation in longitudinal MRI data
Yixing Huang, Christoph Bert, Philipp Sommer +10
Brain metastases occur frequently in patients with metastatic cancer. Early and accurate detection of brain metastases is very essential for treatment planning and prognosis in rad…