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Estimating fat, paste and gas in a proving Danish paste by MRI – Description of the method and evaluation of its performances (bias and accuracy, sensitivity threshold)

机译:通过mRI估算丹麦糊状物中的脂肪,糊状物和气体 - 描述方法并评估其性能(偏差和准确度,灵敏度阈值)

摘要

This paper presents a method to characterize the development of the structures of puff pastries during proving using MRI. Since the resolution is large, each pixel contains an unknown proportion of three components: fat, paste and gas. The signal to noise ratio is low since gas which reaches 80% at the end of proving gives no signal. The signal is the sum of reference signals, corresponding to pixels filled with one component, weighted by the proportions. The reference signals were supposed to be known. We adopted an edge-preserving approach based on the minimization of a penalized least-square criterion. This criterion is the weighted sum of a term accounting for the fidelity to data and a regularization term. The minimization of the criterion is based on a non-linear conjugate gradient algorithm. The settings of the weights of the two terms is based on simulations. Then simulation results are presented. The mean error was similar with or without regularization and depended on the components and their proportion (less that 1% up to 6%). Fat and gas proportions were overestimated, paste proportion was underestimated. The dispersion of the results was lower with regularization (from 0.3% up to 1.5 %). Monte-Carlo simulations showed that these results were not influenced very much by the uncertainty on the reference signals at the end of the proving. Larger uncertainties were found at the beginning of proving. We showed that the regularization of the solutions did improve the visualization of the structures confirming the interest of this approach.We also found that layers down to 40 microns thick and bubbles of which size exceeded 2.5mm could be easily distinguished in fat and gas proportion maps respectively. Experiments on genuine MRI images of Danish paste confirmed the results obtained with the simulation study. We were able to validate the method at the scale of the Danish paste by observing the evolution of the sum of the fat proportion over time, as well as the evolution of the gas content compared with the evolution of the size of the pastry. This confirmed the possibility to use the method to study the proving of a Danish paste.
机译:本文提出了一种方法来表征使用MRI证明过程中的酥油结构的发展。由于分辨率很高,因此每个像素包含未知比例的三种成分:脂肪,糊状物和气体。信噪比低,因为在试验结束时达到80%的气体没有信号。该信号是参考信号的总和,对应于由一个分量填充的像素,并按比例加权。参考信号应该是已知的。我们基于最小化惩罚最小二乘准则的最小化采用了一种边缘保留方法。该标准是考虑数据保真度的项和正则项的加权总和。准则的最小化基于非线性共轭梯度算法。这两项的权重设置是基于模拟的。然后给出了仿真结果。无论是否进行正则化,平均误差都相似,并且取决于组件及其比例(从不到1%到6%)。脂肪和气体的比例被高估,糊剂的比例被低估。结果的离散度随着正则化而降低(从0.3%到1.5%)。蒙特卡洛模拟显示,在证明的最后,这些结果不受参考信号不确定性的很大影响。证明开始时发现较大的不确定性。我们发现解决方案的正则化确实改善了结构的可视化,证实了此方法的重要性。我们还发现,在脂肪和气体比例图中可以轻松区分厚度小于40微米的层和尺寸超过2.5毫米的气泡分别。丹麦糊剂的真实MRI图像实验证实了通过仿真研究获得的结果。通过观察随时间变化的脂肪比例总和的变化以及与糕点尺寸变化相比的含气量变化,我们能够在丹麦糊状食品的规模上验证该方法。这证实了使用该方法研究丹麦糊状物的证明的可能性。

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