Interpretable Mathematical Model-guided Ultrasound Prostate Contour Extraction Using Data Mining Techniques

Tao Peng, Jing Zhao, Jing Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Among all image features, the contour is one of the most critical features for displaying the shape of the object intuitively. Due to unseen/missing regions of transrectal ultrasound images caused by imaging artifacts and limited field of view, accurate and robust ultrasound prostate contour extraction is challenging. Hence, we propose a triple cascaded framework for ultrasound prostate contour extraction using a few existing points as the prior. The proposed scheme contains two types of data mining: principal curve-based and machine learning-based methods. The first stage is using an improved polygonal segment method to obtain a contour composed of line segments connected by sorted vertices, where only a few radiologist-defined seed points are used as the prior. The second stage is to achieve an optimal machine learning-based approach based on an improved differential evolution-based method. The third stage is to find a map function (realized by the machine learning-based method) to generate the smooth contour represented by the output of neural network (i.e., optimized vertices) to match the ground truth contour. Our results demonstrated that the performance of the proposed method outperformed several other state-of-the-art methods.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
EditorsYufei Huang, Lukasz Kurgan, Feng Luo, Xiaohua Tony Hu, Yidong Chen, Edward Dougherty, Andrzej Kloczkowski, Yaohang Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1037-1044
Number of pages8
ISBN (Electronic)9781665401265
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 - Virtual, Online, United States
Duration: Dec 9 2021Dec 12 2021

Publication series

NameProceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

Conference

Conference2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Country/TerritoryUnited States
CityVirtual, Online
Period12/9/2112/12/21

Keywords

  • Contour extraction
  • Data mining techniques
  • Interpretable mathematical model
  • Machine learning
  • Principal curve

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Biomedical Engineering
  • Health Informatics
  • Information Systems and Management

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