A Novel Fusion of Radiomics and Semantic Features: MRI-Based Machine Learning in Distinguishing Pituitary Cystic Adenomas from Rathke’s Cleft Cysts-Reference-Cited by-同舟云学术

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

Published:2024 Issue:1 Volume:108 Page:
ISSN:2514-8281
Container-title:Journal of the Belgian Society of Radiology
language:en
Short-container-title:

Author:

Taslicay Ceylan Altintas^ORCID,Dervisoglu Elmire^ORCID,Ince Okan^ORCID,Mese Ismail^ORCID,Taslicay Cengizhan^ORCID,Bayrak Busra Yaprak^ORCID,Cabuk Burak^ORCID,Anik Ihsan^ORCID,Ceylan Savas^ORCID,Anik Yonca^ORCID

Publisher

Ubiquity Press, Ltd.

Reference21 articles.

1. Pituitary adenomas—practical approach to the diagnosis and the changes in the 2017 WHO classification;Cesk Patol,2019

2. Pituitary MRI standard and advanced sequences: Role in the diagnosis and characterization of pituitary adenomas;J Clin Endocrinol Metab,2022

3. Differentiation between cystic pituitary adenomas and Rathke cleft cysts: A diagnostic model using MRI;AJNR Am J Neuroradiol,2015

4. MRI-based classification of Rathke’s cleft cyst and its clinical implication;Brain Tumor Res Treat,2023

5. Diagnostic significance of intracystic nodules on MRI in Rathke’s cleft cyst;Int J Endocrinol,2012

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