Photoacoustic image denoising using dictionary learning

Syahril Siregar, Yoshifumi Saijo

研究成果: Conference contribution

抄録

Photoacoustic (PA) imaging is the biomedical imaging modality to visualize the biological object with high contrast, high spatial and temporal resolutions. The PA image is degraded due to several parameters such as random noise, frequency, transducer, and laser components. A band-pass filter does not completely remove the noise since the noise is distributed in the bandwidth frequency. In this paper, we propose noise removal method for PA image by applying dictionary learning method. The algorithm is applied to PA images of micropipe filled carbon nanotube and in vivo mice ear. We estimated the optimum input parameters to implement dictionary learning denoising method on PA image. Our results declared that the proposed denoising method using dictionary learning enhances the quality of PA image.

本文言語English
ホスト出版物のタイトルProceedings of 2018 3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018
出版社Association for Computing Machinery
ページ34-37
ページ数4
ISBN(電子版)9781450364362
DOI
出版ステータスPublished - 2018 8 22
イベント3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018 - Seoul, Korea, Republic of
継続期間: 2018 8 222018 8 24

出版物シリーズ

名前ACM International Conference Proceeding Series

Other

Other3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018
国/地域Korea, Republic of
CitySeoul
Period18/8/2218/8/24

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信

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