Improvement of Low-dose MDCT Images by Applying a Novel Adaptive Median Filter with Local Averaging

Deng, Jiehang; Hiratsuka, Kouichirou; Ishida, Tomokazu; Shirai, Haruhiko; Kuroiwa, Jousuke; Odaka, Tomohiro; Ogura, Hisakazu

doi:10.1080/1931308x.2009.10644169

Cited by 1 publication

(3 citation statements)

References 17 publications

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“…The sharp degree near the tumor edge remains well in the voxel value profiles of 3D AMLA. That is consistent with the results in paper [10].…”

Section: Resultssupporting

confidence: 94%

“…To calculate decided according to these three types [10]. n R med xyz S , is set at the median value of S med in this paper.…”

Section: A the Optimized Adaptive Median Filter With Local Averagingmentioning

confidence: 99%

“…Therefore, how to design filtering methods for reducing the quantum noise according to the size and the distribution of voxel value of small regions being suspected of tumors is a serious issue. We previously proposed a novel feature preserving strategy --3D adaptive median filter with local averaging (3D AMLA) [10]. In that study, we used computer-simulated clinical hepatic datasets to achieve smoothness and sharpness.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Filtering Effects Based on Low Dose 3D Hepatic MDCT Images by Applying an Optimized Feature Preserving Strategy

Deng

Zheng

Lv³

et al. 2012

2012 Fourth International Conference on Digital Home

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The X-ray exposure of hepatic MDCT (Multidetector-Row Computed Tomography) images threatens human health. In this paper, the 3D adaptive median filter with local averaging is optimized to improve the image quality of low dose hepatic MDCT images. The modified strategy is designed according to the subtle texture of a hepatic tumor. Filtering experiments are based on phantom images with different dose levels and clinical hepatic ones with a certain dose level. Qualitative and quantitative evaluations show that the x-ray exposure can be reduced to 60% at least without compromising the quality of diagnostic images.

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“…The sharp degree near the tumor edge remains well in the voxel value profiles of 3D AMLA. That is consistent with the results in paper [10].…”

Section: Resultssupporting

confidence: 94%

“…To calculate decided according to these three types [10]. n R med xyz S , is set at the median value of S med in this paper.…”

Section: A the Optimized Adaptive Median Filter With Local Averagingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Filtering Effects Based on Low Dose 3D Hepatic MDCT Images by Applying an Optimized Feature Preserving Strategy

Deng

Zheng

Lv³

et al. 2012

2012 Fourth International Conference on Digital Home

Self Cite

View full text Add to dashboard Cite

show abstract

Improvement of Low-dose MDCT Images by Applying a Novel Adaptive Median Filter with Local Averaging

Cited by 1 publication

References 17 publications

Analysis of Filtering Effects Based on Low Dose 3D Hepatic MDCT Images by Applying an Optimized Feature Preserving Strategy

Analysis of Filtering Effects Based on Low Dose 3D Hepatic MDCT Images by Applying an Optimized Feature Preserving Strategy

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