Swift prediction of personalized head and chest organ doses from CT examinations via neural networks with optimized quantity of hidden layers and radiomics features

Swift prediction of personalized head and chest organ doses from CT examinations via neural networks with optimized quantity of hidden layers and radiomics features

Objective: To utilize radiomics features to enhance the prediction of personalized organ doses from CT scans, in order to explore methods for improving neural network-based models. Methods: Patient CT DICOM files were processed using DeepViewer to define regions of interest (ROIs) in their organs. R...

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Bibliographic Details
Main Authors: Wencheng Shao, Xin Lin, Ying Huang, Liangyong Qu, Weihai Zhuo, Haikuan Liu
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Radiation Medicine and Protection
Subjects:
CT
Personalized organ dose
Radiomics features
Neural network
Optimization
Online Access:http://www.sciencedirect.com/science/article/pii/S2666555725000218
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