Automated segmentation of meningioma from contrast-enhanced T1-weighted MRI images in a case series using a marker-controlled watershed segmentation and fuzzy C-means clustering machine learning algorithm

INTRODUCTION AND IMPORTANCE: Accurate segmentation of meningiomas from contrast-enhanced T1-weighted (CE T1-w) magnetic resonance imaging (MRI) is crucial for diagnosis and treatment planning. Manual segmentation is time-consuming and prone to variability. To evaluate an automated segmentation appro...

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Detalles Bibliográficos
Autores principales: Mohammadi, Sana, Ghaderi, Sadegh, Ghaderi, Kayvan, Mohammadi, Mahdi, Pourasl, Masoud Hoseini
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Case Series
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10514425/
https://www.ncbi.nlm.nih.gov/pubmed/37716060
http://dx.doi.org/10.1016/j.ijscr.2023.108818

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10514425/
https://www.ncbi.nlm.nih.gov/pubmed/37716060
http://dx.doi.org/10.1016/j.ijscr.2023.108818

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