Anatomical position‐guided auto‐segmentation and dosimetric evaluation of vestibular schwannomas in gamma knife radiosurgery
This study showed that embedding a VS-specific anatomical information significantly enhances DLAS accuracy and efficiency, supporting routine GK-SRS planning even on CPU-only workstations. APG can be integrated into various deep-learning networks through channel-wise concatenation.
Authors
- C. Lee (ORCID: https://orcid.org/0009-0003-9015-3528)
- Shanti Marasini (ORCID: https://orcid.org/0000-0003-0713-4418)
- Eunsu Kim
- Taeho Kim (ORCID: https://orcid.org/0000-0001-9809-9587)
- Young‐Cheol Yoon (ORCID: https://orcid.org/0000-0003-3017-5533)
- Jin Sung Kim
- Alex Macintyre
Institutions
- Yonsei University (KR)
- Washington University in St. Louis (US)
- INTRASOFT International (Luxembourg) (LU)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1002/mp.70082
- Primary Topic
- Meningioma and schwannoma management
- Type
- article
- Field-Weighted Citation Impact
- 0.00