Deep Texture Analysis—Enhancing CT Radiomics Features for Prediction of Head and Neck Cancer Treatment Outcomes: A Machine Learning Approach

Deep Texture Analysis—Enhancing CT Radiomics Features for Prediction of Head and Neck Cancer Treatment Outcomes: A Machine Learning Approach

(1) Background: Some cancer patients do not experience tumour shrinkage but are still at risk of experiencing unwanted treatment side effects. Radiomics refers to mining biomedical images to quantify textural characterization. When radiomics features are labelled with treatment response, retrospecti...

Full description

Bibliographic Details
Main Authors: Aryan Safakish, Lakshmanan Sannachi, Amir Moslemi, Ana Pejović-Milić, Gregory J. Czarnota
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Radiation
Subjects:
radiomics
head and neck cancer
deep texture analysis
texture of texture
response prediction
texture features
Online Access:https://www.mdpi.com/2673-592X/4/1/5

Internet

https://www.mdpi.com/2673-592X/4/1/5

Similar Items