CNN-based automatic segmentations and radiomics feature reliability on contrast-enhanced ultrasound images for renal tumors

OBJECTIVE: To investigate the feasibility and efficiency of automatic segmentation of contrast-enhanced ultrasound (CEUS) images in renal tumors by convolutional neural network (CNN) based models and their further application in radiomic analysis. MATERIALS AND METHODS: From 94 pathologically confir...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Yin, Chen, Fei, Liang, Hongmei, Bai, Yun, Wang, Zhen, Zhao, Lei, Ma, Sai, Niu, Qinghua, Li, Fan, Xie, Tianwu, Cai, Yingyu
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/PMC10272725/
https://www.ncbi.nlm.nih.gov/pubmed/37333811
http://dx.doi.org/10.3389/fonc.2023.1166988

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10272725/
https://www.ncbi.nlm.nih.gov/pubmed/37333811
http://dx.doi.org/10.3389/fonc.2023.1166988

Ejemplares similares