Towards Precision Medicine in Sinonasal Tumors: Low-Dimensional Radiomic Signature Extraction from MRI

Towards Precision Medicine in Sinonasal Tumors: Low-Dimensional Radiomic Signature Extraction from MRI

<b>Background:</b> Sinonasal tumors are rare, accounting for 3–5% of head and neck neoplasms. Machine learning (ML) and radiomics have shown promise in tumor classification, but current models lack detailed morphological and textural characterization. <b>Methods:</b> This stu...

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Bibliographic Details
Main Authors: Riccardo Biondi, Giacomo Gravante, Daniel Remondini, Sara Peluso, Serena Cominetti, Francesco D’Amore, Maurizio Bignami, Alberto Daniele Arosio, Nico Curti
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Diagnostics
Subjects:
radiomic
medical image analysis
feature selection
machine learning
otorhinolaryngology
Online Access:https://www.mdpi.com/2075-4418/15/13/1675
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https://www.mdpi.com/2075-4418/15/13/1675

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