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

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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Bibliographic Details
Main Authors: Tao Peng, Caiyin Tang, Yiyun Wu, Jing Cai
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Oncology
Subjects:
accurate prostate segmentation
transrectal ultrasound
principal curve
constraint closed polygonal segment model
improved differential evolution-based method
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.878104/full

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https://www.frontiersin.org/articles/10.3389/fonc.2022.878104/full

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