Artificial intelligence based semi-automatic segmentation for orbital tumor preoperative modeling
Our study utilized 3DSlicer to semi-automatically develop three-dimensional reconstructions of each class of benign orbital tumors as designated by ORBIT criteria. These reconstructions may provide additional quantitative and qualitative data regarding these tumors, their resectability, and the potential surgical approaches required.
Authors
- Margaret B. Mitchell (ORCID: https://orcid.org/0000-0002-8723-7670)
- Benjamin S. Bleier (ORCID: https://orcid.org/0000-0003-0783-8861)
- Ryan A. Bartholomew (ORCID: https://orcid.org/0000-0002-8310-3544)
- Angela Y. Zhu (ORCID: https://orcid.org/0000-0002-3010-8464)
- Barak Ringel (ORCID: https://orcid.org/0000-0003-3355-4651)
Institutions
- Massachusetts Eye and Ear Infirmary (US)
- Harvard University (US)
- John Brown University (US)
Publication Details
- Journal
- Orbit
- Published
- 2025-02-28
- DOI
- https://doi.org/10.1080/01676830.2025.2470359
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36