Spectral Entropic Radiomics Feature Extraction (SERFE): an adaptive approach for glioblastoma disease classification

Spectral Entropic Radiomics Feature Extraction (SERFE): an adaptive approach for glioblastoma disease classification

IntroductionRadiomics-based glioblastoma classification demands feature extraction techniques that can effectively capture tumor heterogeneity while maintaining computational efficiency. Conventional tools such as PyRadiomics and CaPTk rely on extensive handcrafted feature sets, which often result i...

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Bibliographic Details
Main Authors: V. L. Sowmya, A. Bharathi Malakreddy, Santhi Natarajan, N. Prathik, I. S. Rajesh
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Artificial Intelligence
Subjects:
spectral radiomics
entropy-weighted feature selection
graph-theoretic encoding
adaptive radiomics modelling
glioblastoma classification
TCIA-based radiomics
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2025.1583079/full
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https://www.frontiersin.org/articles/10.3389/frai.2025.1583079/full

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