Automatic renal mass segmentation and classification on CT images based on 3D U-Net and ResNet algorithms

PURPOSE: To automatically evaluate renal masses in CT images by using a cascade 3D U-Net- and ResNet-based method to accurately segment and classify focal renal lesions. MATERIAL AND METHODS: We used an institutional dataset comprising 610 CT image series from 490 patients from August 2009 to August...

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Detalles Bibliográficos
Autores principales: Zhao, Tongtong, Sun, Zhaonan, Guo, Ying, Sun, Yumeng, Zhang, Yaofeng, Wang, Xiaoying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233136/
https://www.ncbi.nlm.nih.gov/pubmed/37274226
http://dx.doi.org/10.3389/fonc.2023.1169922

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10233136/
https://www.ncbi.nlm.nih.gov/pubmed/37274226
http://dx.doi.org/10.3389/fonc.2023.1169922

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