Abstract:
Dual high and low energy images of Dual Energy X-ray Absorptiometry (DEXA) suffer from noises due to the use of weak amount of X-rays. Denoising these DEXA images could b...Show MoreMetadata
Abstract:
Dual high and low energy images of Dual Energy X-ray Absorptiometry (DEXA) suffer from noises due to the use of weak amount of X-rays. Denoising these DEXA images could be a key process to enhance and improve a Bone Mineral Density (BMD) map which is derived from a pair of high and low energy images. This could further improve the accuracy of diagnosis of bone fractures, osteoporosis, and etc. In this paper, we present a denoising technique for dual high and low energy images of DEXA via non-local means filter (NLMF). The noise of dual DEXA images is modeled based on both source and detector noises of a DEXA system. Then, the parameters of the proposed NLMF are optimized for denoising utilizing the experimental data from uniform phantoms. The optimized NLMF is tested and verified with the DEXA images of the uniform phantoms and real human spine. The quantitative evaluation shows the improvement of Signal-to-Noise Ratio (SNR) for the high and low phantom images on the order of 30.36% and 27.02% and for the high and low real spine images on the order of 22.28% and 33.43%, respectively. Our work suggests that denoising via NLMF could be a key preprocessing process for clinical DEXA imaging.
Published in: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Date of Conference: 11-15 July 2017
Date Added to IEEE Xplore: 14 September 2017
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PubMed ID: 29059937