Motion-blind blur removal for CT images with Wasserstein Generative Adversarial Networks Conference Paper

  


Authors: Lyu, Y.; Jiang, W.; Lin, Y.; Voros, L.; Zhang, M.; Mueller, B.; Mychalczak, B.; Song, Y.
Title: Motion-blind blur removal for CT images with Wasserstein Generative Adversarial Networks
Conference Title: 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI 2018)
Abstract: Advanced deblurring techniques for computed tomography (CT) images are necessary and crucial to the improvement of accuracy of patient diagnosis in radiology and patient setup and treatment response assessment in radiation oncology. Currently, medical image deblurring is a challenging technical problem due to the unpredictability of patient motion. This paper introduces a new method of computed tomography image deblurring based on Conditional Generative Adversarial Networks (CGAN) that have been broadly implemented in computer vision research. A Wasserstein Generative Adversarial Network (WGAN) with adversarial loss and l1 perceptual loss was proposed and trained by a blur-sharp image pair dataset created in-house and evaluated by Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM). These experiments showed the effectiveness of the approach, which outperforms other competing deblurring techniques both quantitatively and qualitatively. © 2018 IEEE.
Keywords: treatment response; oncology; image enhancement; computerized tomography; medical imaging; computed tomography images; radiation oncology; diagnosis; patient treatment; biomedical engineering; signal to noise ratio; image deblurring; adversarial networks; patient diagnosis; peak signal to noise ratio; structural similarity indices (ssim)
Journal Title Proceedings of the 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI 2018)
Conference Dates: 2018 Oct 13-15
Conference Location: Beijing, China
ISBN: 978-1-5386-7604-2
Publisher: IEEE  
Date Published: 2018-01-01
Start Page: 8633203
Language: English
DOI: 10.1109/cisp-bmei.2018.8633203
PROVIDER: scopus
DOI/URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062840535&doi=10.1109%2fCISP-BMEI.2018.8633203&partnerID=40&md5=bb040cffae2868c9ce7179ae481dffad
Notes: Source: Scopus
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MSK Authors
  1. Borys Mychalczak
    97 Mychalczak
  2. Boris A Mueller
    104 Mueller
  3. Laszlo Voros
    22 Voros
  4. Yulin Song
    116 Song
  5. Miao Zhang
    19 Zhang
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