ArticleInternational journal of computer assisted radiology and surgery2018
A photon recycling approach to the denoising of ultra-low dose X-ray sequences.
Article in International journal of computer assisted radiology and surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Real-time algorithm for Poissonian noise reduction in low-dose fluoroscopy: performance evaluation.Biomedical engineering online · 2019Article
- Preliminary results of DSA denoising based on a weighted low-rank approach using an advanced neurovascular replication system.International journal of computer assisted radiology and surgery · 2019Article
- An analytical approach for the simulation of realistic low-dose fluoroscopic images.International journal of computer assisted radiology and surgery · 2019Article
- Robust navigation support in lowest dose image setting.International journal of computer assisted radiology and surgery · 2019Article
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8 authors.
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Abstract
purposeClinical 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.
methodsOur 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.
resultsThe algorithm has been evaluated on 500 clinical images (7 patients, 20 sequences, 3 clinical sites), taken at ultra-low dose levels, i.e. 50% of the standard low dose level, during electrophysiology procedures. An average improvement in the contrast-to-noise ratio (CNR) by a factor of around 3.5 has been found. This is associated with an image quality achieved at around 12 (square of 3.5) times the ultra-low dose level. Qualitative evaluation by X-ray image quality experts suggests that the method produces denoised images that comply with the required image quality criteria.
conclusionThe results are consistent with the number of patches used, and they demonstrate that it is possible to use motion estimation techniques and "recycle" photons from previous frames to improve the image quality of the current frame. Our results are comparable in terms of CNR to Video Block Matching 3D-a state-of-the-art denoising method. But qualitative analysis by experts confirms that the denoised ultra-low dose X-ray images obtained using our method are more realistic with respect to appearance.
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