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Ultrasound denoising using the pix2pix GAN

Abstract #

The use of ultrasound (US) as an imaging technique is essential for the diagnosis of atherosclerotic cardiovascular disease (ASCVD), which depends on US images of the carotid artery. However, US images are plagued by a specific type of noise called Speckle noise, which lowers image quality dramatically. As an attempt to improve US image quality, the use of a generative adversarial network (GAN) is explored. The GAN chosen for this is the pix2pix model and the dataset used for training is composed of images containing simple geometric shapes of various scales and their equivalent corrupted with Speckle noise following the Log-Compression model. The results of this GAN are displayed and a noticeable improvement can be verified in the image quality.


Bibtex #

    abbr            = {RECPAD},
    author          = {Afonso Raposo and António Azeitona and Manya Afonso and João Sanches},
    title           = {Ultrasound denoising using the pix2pix GAN},
    booktitle       = {27th Portuguese Conference on Pattern Recognition},
    year            = {2021},
    month           = {11},
    organization    = {RECPAD},
    address         = {Évora, Portugal},
    pages           = {91-92},