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A scatter correction method for dual-energy digital mammography: Monte Carlo simulation

机译:双能数字乳腺X射线摄影的散射校正方法:蒙特卡洛模拟

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PURPOSE: To develop a novel scatter correction method without additional patient dose for dual-energy digitalmammography(DEDM) to reduce scatter's impacts and enhance microcalcification detectability in dual-energy X-ray subtraction image. METHODS: Combining scatter radiation is lower spatial frequency component and calcifications are sparsely distributed in digital mammogram, we develop a new scatter correction strategy. First, an adaptive sampling scheme is presented to find possible noncalcification (zero calcification) pixels. Then the maximum likelihood expectation maximization (MLEM) algorithm is applied to evaluate initial scatter surface. The accurate scatter radiation of sampling pixels is obtained by solving dual-energy computational formula with zero calcification constraint and scatter surface constraint. RESULTS: After scatter correction, the scatter-to-primary ratio (SPR) of wedge phantom is reduced from ~36.0% to ~3.1% for low-energy (LE) image and ~29.6% to ~0.6% for high-energy (HE) image. For step phantom, the SPR is reduced from~42.1% and ~30.3% to ~3.9% and ~0.9% for LE and HE image, respectively. The calcification contrast-to-noise ratio is improved by two orders of magnitudes in calcification images. CONCLUSIONS: The proposed method shows an excellent performance on scatter reduction and calcification detection. Compared with hardware based scatter correction strategy, our method need no extra exposure and is easy to implementation.
机译:目的:开发一种无需额外患者剂量的双能量数字乳房X线摄影(DEDM)的新颖的散射校正方法,以减少散射的影响并增强双能量X射线减影图像中的微钙化可检测性。方法:结合散射辐射是较低的空间频率分量,钙化在数字乳腺X线照片中稀疏分布,我们开发了一种新的散射校正策略。首先,提出了一种自适应采样方案以查找可能的非钙化(零钙化)像素。然后将最大似然期望最大化(MLEM)算法应用于评估初始散射面。通过求解零钙化约束和散射表面约束的双能计算公式,可以得到采样像素的精确散射辐射。结果:散点校正后,低能像图像的楔形体模的原色散度从〜36.0%降低到〜3.1%,高能像片的散射原色比从〜29.6%降低到〜0.6%( HE)图片。对于步幻影,对于LE和HE图像,SPR分别从〜42.1%和〜30.3%减小到〜3.9%和〜0.9%。在钙化图像中,钙化对比噪声比提高了两个数量级。结论:所提出的方法在散射减少和钙化检测方面表现出优异的性能。与基于硬件的散射校正策略相比,我们的方法不需要额外的曝光,并且易于实现。

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