Segmentation of aliasing artefacts in ultrasound color flow imaging using convolutional neural networks

Hassan Nahas, Takuro Ishii, Adrian Chee, Billy Yiu, Alfred Yu

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Color flow imaging is a biomedical ultrasound modality used to visualize blood flow dynamics in the blood vessels, which are correlated with cardiovascular function and pathology. This is however done through a pulsed echo sensing mechanism and thus flow measurements can be corrupted by aliasing artefacts, hindering its application. While various methods have attempted to address these artefacts, there is still demand for a robust and flexible solution, particularly at the stage of identifying the aliased regions in the imaging view. In this paper, we investigate the application of convolutional neural networks to segment aliased regions in color flow images due to their strength in translation-invariant learning of complex features. Relevant ultrasound features including phase shifts, speckle images and optical flow were generated from ultrasound data obtained from anthropomorphic flow models. The investigated neural networks all showed strong performance in terms of precision, recall and intersection over union while revealing the important ultrasound features that improved detection. This study paves the way for sophisticated dealiasing algorithms in color flow imaging.

本文言語English
ホスト出版物のタイトルImage Analysis and Recognition - 16th International Conference, ICIAR 2019, Proceedings
編集者Fakhri Karray, Alfred Yu, Aurélio Campilho
出版社Springer Verlag
ページ452-461
ページ数10
ISBN(印刷版)9783030272715
DOI
出版ステータスPublished - 2019
外部発表はい
イベント16th International Conference on Image Analysis and Recognition, ICIAR 2019 - Waterloo, Canada
継続期間: 2019 8 272019 8 29

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11663 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference16th International Conference on Image Analysis and Recognition, ICIAR 2019
CountryCanada
CityWaterloo
Period19/8/2719/8/29

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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