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
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666555725000218
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