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3D Density Estimation in Digital Breast Tomosynthesis —Application to Needle Path Planning for Breast Biopsy

机译:数字乳房造成的3D密度估计 - 乳腺活检针对针路径规划的应用

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Needle insertion planning for digital breast tomosynthesis (DBT) guided biopsy has the potential to improve patient comfort and intervention safety. However, a relevant planning should take into account breast tissue deformation and lesion displacement during the procedure. Deformable models, like finite elements, use the elastic characteristics of the breast to evaluate the deformation of tissue during needle insertion. This paper presents a novel approach to locally estimate the Young's modulus of the breast tissue directly from the DBT data. The method consists in computing the fibroglandular percentage in each of the acquired DBT projection images, then reconstructing the density volume. Finally, this density information is used to compute the mechanical parameters for each finite element of the deformable mesh, obtaining a heterogeneous DBT based breast model. Preliminary experiments were performed to evaluate the relevance of this method for needle path planning in DBT guided biopsy. The results show that the heterogeneous DBT based breast model improves needle insertion simulation accuracy in 71% of the cases, compared to a homogeneous model or a binary fat/fibroglandular tissue model.
机译:针对数字乳房断层合成的针插入规划(DBT)引导活检有可能提高患者的舒适性和干预安全性。然而,相关规划应考虑到过程中的乳腺组织变形和病变位移。可变形型号,如有限元,使用乳房的弹性特性来评估针插入期间组织的变形。本文提出了一种新颖的方法,可以直接从DBT数据划分乳房组织的杨氏模量。该方法在于计算每个获取的DBT投影图像中的纤维族百分比,然后重建密度体积。最后,该密度信息用于计算可变形网格的每个有限元件的机械参数,获得基于异构的DBT基乳房模型。进行初步实验以评估该方法在DBT引导活检中针对针路径规划的相关性。结果表明,与均匀模型或二元脂肪/纤维族组织模型相比,非均相DBT基乳房模型在71%的情况下提高了针插入模拟精度。

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