AI-Driven innovations for managing ependymoma in neurosurgery
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10143-024-02871-6.pdf
Reference10 articles.
1. Zamora EA, Alkherayf F (2024) In: StatPearls (ed) Ependymoma. StatPearls Publishing: Treasure Island (FL);
2. Quon JL, Bala W, Chen LC et al (2020) Deep Learning for Pediatric Posterior Fossa Tumor Detection and classification: a multi-institutional study. AJNR Am J Neuroradiol 41:1718–1725. https://doi.org/10.3174/ajnr.A6704
3. Celano E, Salehani A, Malcolm JG, Reinertsen E, Hadjipanayis CG (2016) Spinal cord ependymoma: a review of the literature and case series of ten patients. J Neurooncol 128:377–386. https://doi.org/10.1007/s11060-016-2135-8
4. Kokkinos V, Chatzisotiriou A, Seimenis I (2023) Functional Magnetic Resonance Imaging and diffusion Tensor Imaging-Tractography in Resective Brain surgery: Lesion Coverage strategies and patient outcomes. Brain Sci 13:1574. https://doi.org/10.3390/brainsci13111574
5. Williams S, Layard Horsfall H, Funnell JP et al (2021) Artificial Intelligence in Brain Tumour Surgery—An emerging paradigm. Cancers (Basel) 13:5010. https://doi.org/10.3390/cancers13195010
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