Journal Q2

A photon recycling approach to the denoising of ultra-low dose X-ray sequences

Sai Gokul Hariharan, Norbert Strobel, Christian Kaethner, Markus Kowarschik, Stefanie Demirci, Shadi Albarqouni, Rebecca Fahrig, Nassir Navab

International journal of computer assisted radiology and surgery, 2018

Abstract

Clinical procedures that make use of fluoroscopy may expose patients as well as the clinical staff (throughout their career) to non-negligible doses of radiation. The potential consequences of such exposures fall under two categories, namely stochastic (mostly cancer) and deterministic risks (skin injury). According to the “as low as reasonably achievable” principle, the radiation dose can be lowered only if the necessary image quality can be maintained.Our work improves upon the existing patch-based denoising algorithms by utilizing a more sophisticated noise model to exploit non-local self-similarity better and this in turn improves the performance of low-rank approximation. The novelty of the proposed approach lies in its properly designed and parameterized noise model and the elimination of initial estimates. This reduces the computational cost significantly.The algorithm has been …

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Research themes

Keywords

Radiology

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Cite (BibTeX)
@article{hariharan2018photon,
 author = {Hariharan, Sai Gokul and Strobel, Norbert and Kaethner, Christian and Kowarschik, Markus and Demirci, Stefanie and Albarqouni, Shadi and Fahrig, Rebecca and Navab, Nassir},
 journal = {International journal of computer assisted radiology and surgery},
 number = {6},
 pages = {847--854},
 publisher = {Springer International Publishing},
 title = {A photon recycling approach to the denoising of ultra-low dose X-ray sequences},
 volume = {13},
 year = {2018}
}

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