Two-Step Semiautomated Classification of Choroidal Metastases on MRI: Orbit Localization via Bounding Boxes Followed by Binary Classification via Evolutionary Strategies
The semiautomated pipeline from brain MRI slices to choroidal metastasis classification demonstrates the utility of a sequential localization and classification approach, and clinical relevance for identifying small, "corner-of-the-image," easily overlooked lesions. Artificial Intelligence Level of Evidence: 5B.
Authors
- Hrithwik Shalu (ORCID: https://orcid.org/0000-0002-8944-434X)
- Jiyun Shi (ORCID: https://orcid.org/0000-0001-7220-9637)
- Andrei I. Holodny (ORCID: https://orcid.org/0000-0002-1159-2705)
- Sofia Haque (ORCID: https://orcid.org/0000-0003-4673-9997)
- Joseph N. Stember (ORCID: https://orcid.org/0000-0003-3169-9590)
- Bala McRae‐Posani (ORCID: https://orcid.org/0000-0002-0963-7855)
Institutions
- Memorial Sloan Kettering Cancer Center (US)
- Cornell University (US)
- Indian Institute of Technology Madras (IN)
Publication Details
- Journal
- American Journal of Neuroradiology
- Published
- 2025-09-09
- DOI
- https://doi.org/10.3174/ajnr.a8998
- Primary Topic
- Ocular Oncology and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00