Deep learning-based automatic segmentation of meningioma from T1-weighted contrast-enhanced MRI for preoperative meningioma differentiation using radiomic features.

"Declarations Ethics approval and consent to participateThe study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Institutional Review Board and Ethical Committee of The Harbin Medical University Cancer Hospital. The need for informed consent was waived by the ethics committee of The Harbin Medical University Cancer Hospital, because of the retrospective nature of the study. Consent for publicationNot applicable. Competing interestsThe authors declare no competing interests. Competing interests The authors declare no competing interests."

"Funding This study was sponsored in part by the Haiyan Fund of Harbin Medical University Cancer Hospital (No. JJMS-2023–05). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of this manuscript."