Cardio-pulmonary substructure segmentation of radiotherapy computed tomography images using convolutional neural networks for clinical outcomes analysis

Cardio-pulmonary substructure segmentation of radiotherapy computed tomography images using convolutional neural networks for clinical outcomes analysis

Background and purpose: Radiation dose to the cardio-pulmonary system is critical for radiotherapy-induced mortality in non-small cell lung cancer. Our goal was to automatically segment substructures of the cardio-pulmonary system for use in outcomes analyses for thoracic cancers. We built and valid...

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Bibliographic Details
Main Authors: Rabia Haq, Alexandra Hotca, Aditya Apte, Andreas Rimner, Joseph O. Deasy, Maria Thor
Format: Article
Language:English
Published: Elsevier 2020-04-01
Series:Physics and Imaging in Radiation Oncology
Subjects:
Semantic segmentation
Convolutional neural networks
Cardio-pulmonary
Clinical outcomes
Radiation therapy
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631620300221

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http://www.sciencedirect.com/science/article/pii/S2405631620300221

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