Deep Texture Analysis Enhanced MRI Radiomics for Predicting Head and Neck Cancer Treatment Outcomes with Machine Learning Classifiers

Deep Texture Analysis Enhanced MRI Radiomics for Predicting Head and Neck Cancer Treatment Outcomes with Machine Learning Classifiers

<b>Background:</b> Head and neck cancer treatment does not yield desired outcomes for all patients. This investigation aimed to explore the feasibility of predicting treatment outcomes from routine pre-treatment magnetic resonance images (MRIs). Radiomics features were “mined” and used t...

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Bibliographic Details
Main Authors: Aryan Safakish, Amir Moslemi, Daniel Moore-Palhares, Lakshmanan Sannachi, Ian Poon, Irene Karam, Andrew Bayley, Ana Pejovic-Milic, Gregory J. Czarnota
Format: Article
Language:English
Published: MDPI AG 2024-06-01
Series:Radiation
Subjects:
radiomics
deep texture analysis
cancer treatment
response prediction
machine learning prediction
texture features
Online Access:https://www.mdpi.com/2673-592X/4/2/15

Internet

https://www.mdpi.com/2673-592X/4/2/15

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