The realistic numerical breast model is an important tool for verifying algorithms, improving design concepts, and exploring new technologies related to microwave breast cancer detection. Recently, several numerical breast models have been developed. However, these models do not include the real breast boundary and the chest region, which causes the electromagnetic wave propagation in the breast models to deviate from the actual situation. The proposed breast models in this paper overcome the significant deficiencies of the recent breast models in terms of structure completeness and authenticity. The model construction based on magnetic resonance imaging (MRI) scans is a multistep approach. Firstly, intensity inhomogeneity in MRI images is corrected by an improved nonparametric nonuniform intensity normalization (N4) algorithm. Then, a dual threshold and morphological transformation (DTMT) method is developed to segment the real breast region. Subsequently, a modified maximum inter-class variance (MICV) method is employed to automatically divide the breast region into the fat and the fibroglandular clusters with desired complexity. Finally, the dielectric properties of breast tissues are calculated by a piecewise weighted mapping method. The applicability and effectiveness of the proposed method are verified by constructing four breast models with varying tissue density, shape, and size. The constructed models in this study are significant to achieve reliable and precise effects for microwave breast cancer detection due to the accurate expression of the breast anatomical information and electromagnetic characteristics.

逼真的乳腺数值模型是验证算法，改进设计概念以及探索与微波乳腺癌检测相关的新技术的重要工具。最近，已经开发了几种数值乳腺模型。但是，这些模型不包括实际的乳房边界和胸部区域，这会导致电磁波在乳房模型中的传播偏离实际情况。本文中提出的乳房模型克服了近期乳房模型在结构完整性和真实性方面的重大缺陷。基于磁共振成像（MRI）扫描的模型构建是一种多步骤方法。首先，通过改进的非参数非均匀强度归一化（N4）算法校正MRI图像中的强度不均匀性。然后，开发了双阈值和形态转换（DTMT）方法来分割真实的乳房区域。随后，采用改进的最大类间差异（MICV）方法将乳房区域自动划分为具有所需复杂度的脂肪和纤维腺簇。最后，通过分段加权映射方法计算出乳腺组织的介电性能。通过构建具有不同组织密度，形状和大小的四个乳房模型，验证了该方法的适用性和有效性。由于乳房解剖信息和电磁特性的准确表达，本研究中构建的模型对于实现可靠可靠的微波乳腺癌检测效果具有重要意义。