Volumetric measurement of intracranial meningiomas: a comparison between linear, planimetric, and machine learning with multiparametric voxel-based morphometry methods
Author:
Publisher
Springer Science and Business Media LLC
Subject
Cancer Research,Neurology (clinical),Neurology,Oncology
Link
https://link.springer.com/content/pdf/10.1007/s11060-022-04127-z.pdf
Reference20 articles.
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2. Ogasawara C, Philbrick BD, Adamson DC (2021) Meningioma: a review of epidemiology, pathology, diagnosis, treatment, and future directions. Biomedicines 9:319. https://doi.org/10.3390/biomedicines9030319
3. Opalak CF, Parry M, Rock AK et al (2019) Comparison of ABC/2 estimation and a volumetric computerized method for measurement of meningiomas using magnetic resonance imaging. J Neuro-Oncol 144:275–282. https://doi.org/10.1007/s11060-019-03205-z
4. Fountain DM, Soon WC, Matys T et al (2017) Volumetric growth rates of meningioma and its correlation with histological diagnosis and clinical outcome: a systematic review. Acta Neurochir 159:435–445. https://doi.org/10.1007/s00701-016-3071-2
5. Goldbrunner R, Stavrinou P, Jenkinson MD et al (2021) EANO guideline on the diagnosis and management of meningiomas. Neuro-Oncology 23:1821–1834. https://doi.org/10.1093/neuonc/noab150
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1. Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets;Journal of Medical Internet Research;2023-12-15
2. Performance Test of a Well-Trained Model for Meningioma Segmentation in Health Care Centers: Secondary Analysis Based on Four Retrospective Multicenter Data Sets (Preprint);2022-11-08
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