Semi-Automatic Prostate Segmentation From Ultrasound Images Using Machine Learning and Principal Curve Based on Interpretable Mathematical Model Expression

Accurate prostate segmentation in transrectal ultrasound (TRUS) is a challenging problem due to the low contrast of TRUS images and the presence of imaging artifacts such as speckle and shadow regions. To address this issue, we propose a semi-automatic model termed Hybrid Segmentation Model (H-SegMo...

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Detalles Bibliográficos
Autores principales: Peng, Tao, Tang, Caiyin, Wu, Yiyun, Cai, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209717/
https://www.ncbi.nlm.nih.gov/pubmed/35747834
http://dx.doi.org/10.3389/fonc.2022.878104

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209717/
https://www.ncbi.nlm.nih.gov/pubmed/35747834
http://dx.doi.org/10.3389/fonc.2022.878104

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