A Novel Fusion of Radiomics and Semantic Features: MRI-Based Machine Learning in Distinguishing Pituitary Cystic Adenomas from Rathke's Cleft Cysts

A Novel Fusion of Radiomics and Semantic Features: MRI-Based Machine Learning in Distinguishing Pituitary Cystic Adenomas from Rathke's Cleft Cysts

Objectives: To evaluate the performances of machine learning using semantic and radiomic features from magnetic resonance imaging data to distinguish cystic pituitary adenomas (CPA) from Rathke’s cleft cysts (RCCs). Materials and Methods: The study involved 65 patients diagnosed with either CPA or R...

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Bibliographic Details
Main Authors: Ceylan Altintas Taslicay, Elmire Dervisoglu, Okan Ince, Ismail Mese, Cengizhan Taslicay, Busra Yaprak Bayrak, Burak Cabuk, Ihsan Anik, Savas Ceylan, Yonca Anik
Format: Article
Language:English
Published: Ubiquity Press 2024-02-01
Series:Journal of the Belgian Society of Radiology
Subjects:
cystic pituitary adenomas
machine learning algorithms
magnetic resonance imaging
radiomics
rathke's cleft cysts
Online Access:https://account.jbsr.be/index.php/up-j-jbsr/article/view/3470

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https://account.jbsr.be/index.php/up-j-jbsr/article/view/3470

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