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In this study, we developed a deep learning-based method for automated segmentation of multiple organs on CBCT images which simultaneously performs detection, ...
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CBCT lung multi-OAR segmentation via hierarchical network. April 2022 ... Automatic Segmentation of Lung Noudles using improved U-Net NetWork. November ...
CBCT lung multi-OAR segmentation via hierarchical network. R. Qiu, Y. Lei, J. Shelton, K. Higgins, J. Bradley, T. Liu, A. Kesarwala, and X. Yang.
Conclusion: We demonstrated the feasibility of a synthetic CT-aided deep learning framework for automated delineation of multiple OARs on CBCT. The proposed ...
In this study, a two-in-one deep learning model is investigated for fully-automated CBCT-based segmentation of up to eight OARs in the setting of pancreatic ...
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Aug 2, 2020 · Purpose: Segmentation of organs-at-risk (OARs) is a weak link in radiotherapeutic treatment planning process because the manual contouring ...
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CBCT Lung Multi-OAR Segmentation via Hierarchical Network. Proceedings of SPIE - The International Society for Optical Engineering. 2022 | Conference paper.
A novel deep-learning-based approach with the GAN strategy can automatically and accurately segment multiple OARs in thorax CT images, which could be a ...
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Jul 12, 2020 · Purpose. Segmentation of organs-at-risk (OARs) is a weak link in radiotherapeutic treatment planning process because the manual contouring ...