共 11 条
Evaluating noise reduction techniques while considering anatomical noise in dual-energy contrast-enhanced mammography
被引:6
作者:
Allec, Nicholas
[1
]
Abbaszadeh, Shiva
[1
]
Scott, Chris C.
[1
]
Karim, Karim S.
[1
]
Lewin, John M.
[2
]
机构:
[1] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
[2] Diversified Radiol Colorado Res Inst, Denver, CO 80204 USA
基金:
加拿大自然科学与工程研究理事会;
关键词:
noise reduction;
anatomical noise;
dual-energy imaging;
mammography;
ALGORITHM;
D O I:
10.1118/1.4799841
中图分类号:
R8 [特种医学];
R445 [影像诊断学];
学科分类号:
1002 ;
100207 ;
1009 ;
摘要:
Purpose: The authors describe modifications to previously developed cascaded systems analysis to include the anatomical noise in evaluation of dual-energy noise reduction techniques. Previous models have ignored the anatomical noise in theoretical analysis of noise reduction techniques. The inclusion of anatomical noise leads to more accurate estimation of potential noise reduction improvements and optimization. Methods: The model is applied to dual-energy contrast-enhanced mammography. The effect of linear noise reduction filters on the anatomical noise is taken into account using cascaded systems analysis. The noise model is included in the ideal observer detectability for performance evaluation of the noise reduction techniques. Results: Dual-energy image noise with and without including the effect of anatomical noise in noise reduction technique analysis is reported. The theoretical model is compared with clinical images from a previous dual-energy contrast enhanced mammography clinical study and good agreement is observed. The results suggest that the inclusion of anatomical noise in the evaluation and comparison of noise reduction techniques is highly warranted for more accurate analysis. Conclusions: This work establishes a useful extension to dual-energy cascaded systems analysis for maximizing image quality using noise reduction techniques. The extension includes the effect of linear image filtering, such as that used for noise reduction, on anatomical noise. The results suggest that the inclusion of anatomical noise in the evaluation of noise reduction techniques can lead to more accurate optimization, noise, and performance estimations. (C) 2013 American Association of Physicists in Medicine.
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