Impact of Denoising on Deep-Learning-Based Automatic Segmentation Framework for Breast Cancer Radiotherapy Planning

SIMPLE SUMMARY: We investigated the contouring data of organs at risk from 40 patients with breast cancer who underwent radiotherapy. The performance of denoising-based auto-segmentation was compared with manual segmentation and conventional deep-learning-based auto-segmentation without denoising. D...

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Detalles Bibliográficos
Autores principales: Im, Jung Ho, Lee, Ik Jae, Choi, Yeonho, Sung, Jiwon, Ha, Jin Sook, Lee, Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332287/
https://www.ncbi.nlm.nih.gov/pubmed/35892839
http://dx.doi.org/10.3390/cancers14153581

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332287/
https://www.ncbi.nlm.nih.gov/pubmed/35892839
http://dx.doi.org/10.3390/cancers14153581

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