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researcher

S. Lettmaier

3 papers hereh-index 201.2k citations72 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • physics.med-ph1

identity via Semantic Scholar / OpenAlex

most citedDeep learning for automatic head and neck lymph node level delineation provides expert-level accuracy

32 citations · 44 across the 3 of their papers we have counts for

collaborators

3 papers

eess.IV2023★ 3 cited

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…

physics.med-ph2023★ 9 cited

Benchmarking ChatGPT-4 on ACR Radiation Oncology In-Training (TXIT) Exam and Red Journal Gray Zone Cases: Potentials and Challenges for AI-Assisted Medical Education and Decision Making in Radiation Oncology

Yixing Huang, Ahmed Gomaa, Sabine Semrau +12

The potential of large language models in medicine for education and decision making purposes has been demonstrated as they achieve decent scores on medical exams such as the Unite…

eess.IV2022★ 32 cited

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.