计算机科学
加权
正规化(语言学)
人工智能
模式识别(心理学)
计算机视觉
数据挖掘
放射科
医学
作者
Jonghyun Bae,Zhengguo Tan,Eddy Solomon,Zhengnan Huang,Laura Heacock,Linda Moy,Florian Knöll,Sungheon Kim
摘要
Abstract Purpose To develop a digital reference object (DRO) toolkit to generate realistic breast DCE‐MRI data for quantitative assessment of image reconstruction and data analysis methods. Methods A simulation framework in a form of DRO toolkit has been developed using the ultrafast and conventional breast DCE‐MRI data of 53 women with malignant ( n = 25) or benign ( n = 28) lesions. We segmented five anatomical regions and performed pharmacokinetic analysis to determine the ranges of pharmacokinetic parameters for each segmented region. A database of the segmentations and their pharmacokinetic parameters is included in the DRO toolkit that can generate a large number of realistic breast DCE‐MRI data. We provide two potential examples for our DRO toolkit: assessing the accuracy of an image reconstruction method using undersampled simulated radial k‐space data and assessing the impact of the field inhomogeneity on estimated parameters. Results The estimated pharmacokinetic parameters for each region showed agreement with previously reported values. For the assessment of the reconstruction method, it was found that the temporal regularization resulted in significant underestimation of estimated parameters by up to 57% and 10% with the weighting factor λ = 0.1 and 0.01, respectively. We also demonstrated that spatial discrepancy of and increase to about 33% and 51% without correction for field. Conclusion We have developed a DRO toolkit that includes realistic morphology of tumor lesions along with the expected pharmacokinetic parameter ranges. This simulation framework can generate many images for quantitative assessment of DCE‐MRI reconstruction and analysis methods.
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