Automatic segmentation of rectal tumor on diffusion‐weighted images by deep learning with U‐Net

PURPOSE: Manual delineation of a rectal tumor on a volumetric image is time‐consuming and subjective. Deep learning has been used to segment rectal tumors automatically on T2‐weighted images, but automatic segmentation on diffusion‐weighted imaging is challenged by noise, artifact, and low resolutio...

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Detalles Bibliográficos
Autores principales: Zhu, Hai‐Tao, Zhang, Xiao‐Yan, Shi, Yan‐Jie, Li, Xiao‐Ting, Sun, Ying‐Shi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425941/
https://www.ncbi.nlm.nih.gov/pubmed/34343402
http://dx.doi.org/10.1002/acm2.13381

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425941/
https://www.ncbi.nlm.nih.gov/pubmed/34343402
http://dx.doi.org/10.1002/acm2.13381

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