A deep learning framework for lesion-level treatment response prediction in hodgkin lymphoma using PET/CT tensor radiomics

Abstract Background Accurate prediction of treatment response in Hodgkin lymphoma (HL) is crucial for personalized therapy. The Tensor Radiomics (TR) paradigm advances traditional radiomics by producing and analyzing diverse feature variations, employing tensors computed across multiple parameter co...

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Hauptverfasser:	Mahdie Jajroudi, Hossein Jamalirad, Milad Enferadi, Vahid Roshanravan, Farshad Emami, Parham Geramifar, Saeid Eslami
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	SpringerOpen 2026-06-01
Schriftenreihe:	EJNMMI Physics
Schlagworte:	Tensor radiomics Hodgkin lymphoma PET/CT Deep learning Treatment response prediction
Online-Zugang:	https://doi.org/10.1186/s40658-026-00838-8
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