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Photoacoustic Image Denoising Using Dictionary Learning

Siregar, Syahril LU (2018)
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
host publication
ICBIP 2018
publisher
Association for Computing Machinery (ACM)
external identifiers
  • scopus:85058529001
ISBN
978-1-4503-6436-2
language
English
LU publication?
no
id
994368f5-7b89-4e46-b7a2-b48d3434f048
alternative location
https://dl.acm.org/citation.cfm?id=3278230
date added to LUP
2019-05-08 13:56:38
date last changed
2022-01-31 19:39:39
@inproceedings{994368f5-7b89-4e46-b7a2-b48d3434f048,
  abstract     = {{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.}},
  author       = {{Siregar, Syahril}},
  booktitle    = {{ICBIP 2018}},
  isbn         = {{978-1-4503-6436-2}},
  language     = {{eng}},
  month        = {{08}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{Photoacoustic Image Denoising Using Dictionary Learning}},
  url          = {{https://dl.acm.org/citation.cfm?id=3278230}},
  year         = {{2018}},
}