TY - GEN
T1 - Photoacoustic image denoising using dictionary learning
AU - Siregar, Syahril
AU - Saijo, Yoshifumi
N1 - Publisher Copyright:
© 2018 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2018/8/22
Y1 - 2018/8/22
N2 - 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.
AB - 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.
KW - Dictionary learning
KW - Image denoising
KW - Photoacoustic image
KW - PSNR
UR - http://www.scopus.com/inward/record.url?scp=85058529001&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058529001&partnerID=8YFLogxK
U2 - 10.1145/3278229.3278230
DO - 10.1145/3278229.3278230
M3 - Conference contribution
AN - SCOPUS:85058529001
T3 - ACM International Conference Proceeding Series
SP - 34
EP - 37
BT - Proceedings of 2018 3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018
PB - Association for Computing Machinery
T2 - 3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018
Y2 - 22 August 2018 through 24 August 2018
ER -