Hybrid Radiomics and Machine Learning for Brain Tumors Multi‐Task Classification: An Exploratory Study on Integrating GLCM and Curvelet‐Based Features for Enhanced Accuracy

ABSTRACT Background and Aims Accurate classification of brain tumors is vital for effective treatment planning. Manual assessment of magnetic resonance imaging (MRI) scans is often subjective and time‐consuming. This exploratory study proposes a machine learning approach integrating radiomic feature...

Descripció completa

Dades bibliogràfiques

Autors principals:	Mostafa Jafari, Masoumeh Rahmani, Sanaz Alibabaei, Jafar Fatahiasl, Sasan Razmjoo, Mohammad Javad Tahmasebi Birgani, Marziyeh Tahmasbi
Format:	Artigo
Idioma:	Inglês
Publicat:	Wiley 2025-08-01
Col·lecció:	Health Science Reports
Matèries:	brain tumor classification curvelet transform feature selection GLCM machine learning MRI radiomics
Accés en línia:	https://doi.org/10.1002/hsr2.71195
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!