Computational Breast Anatomy Simulation Using Multi-Scale Perlin Noise.
Computational Breast Anatomy Simulation Using Multi-Scale Perlin Noise.
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DOI：
10.1109/tmi.2021.3087958
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发表时间：
2021-12
影响因子：
10.6
通讯作者：
Maidment ADA
中科院分区：
文献类型：
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作者：
Barufaldi B;Abbey CK;Lago MA;Vent TL;Acciavatti RJ;Bakic PR;Maidment ADA
医学成像的虚拟临床试验（VCT）需要逼真的人体解剖模型。对于乳腺成像中的VCT，提出了一种多尺度Perlin噪声方法，用于在正在进行的乳腺体模开发工作的背景下模拟乳腺组织的解剖结构。四个柏林噪声分布被用来取代体素代表组织隔间和库珀的韧带在乳房模型。使用临床DBT系统配置模拟数字乳腺摄影和断层合成投影。功率谱分析和高阶统计特性，使用拉普拉斯分数熵（LFE）的实质纹理。使用140张临床乳房X线照片和500张体模图像的样本，在体模和患者图像中计算这些客观测量值。使用功率谱低频[0.1，1.0] mm−1区域拟合的曲线斜率计算幂律指数。结果表明，与临床乳房X线照片相比，我们以前和建议的Perlin方法模拟的图像具有相似的幂律谱。对于患者、先前体模和建议体模图像的对数功率谱，计算的幂律指数分别为-3.10、-3.55和-3.46。结果还表明，基于柏林噪声的体模和患者的平均LFE估计值之间的一致性比我们先前的体模和患者的一致性更好。因此，与我们先前的方法相比，所提出的方法大大改善了解剖噪声的模拟，显示出与乳房实质测量的密切一致性。
Virtual clinical trials (VCTs) of medical imaging require realistic models of human anatomy. For VCTs in breast imaging, a multi-scale Perlin noise method is proposed to simulate anatomical structures of breast tissue in the context of an ongoing breast phantom development effort. Four Perlin noise distributions were used to replace voxels representing the tissue compartments and Cooper’s ligaments in the breast phantoms. Digital mammography and tomosynthesis projections were simulated using a clinical DBT system configuration. Power-spectrum analyses and higher-order statistics properties using Laplacian fractional entropy (LFE) of the parenchymal texture are presented. These objective measures were calculated in phantom and patient images using a sample of 140 clinical mammograms and 500 phantom images. Power-law exponents were calculated using the slope of the curve fitted in the low frequency [0.1, 1.0] mm−1 region of the power spectrum. The results show that the images simulated with our prior and proposed Perlin method have similar power-law spectra when compared with clinical mammograms. The power-law exponents calculated are −3.10, −3.55, and −3.46, for the log-power spectra of patient, prior phantom and proposed phantom images, respectively. The results also indicate an improved agreement between the mean LFE estimates of Perlin-noise based phantoms and patients than our prior phantoms and patients. Thus, the proposed method improved the simulation of anatomic noise substantially compared to our prior method, showing close agreement with breast parenchyma measures.