Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis.
Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis.
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DOI：
10.1118/1.4928603
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发表时间：
2015-09
期刊：
影响因子：
3.8
通讯作者：
Shiyu Xu;Jianping Lu;O. Zhou;Ying Chen
中科院分区：
文献类型：
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作者：
Shiyu Xu;Jianping Lu;O. Zhou;Ying Chen
数字乳腺断层合成摄影（DBT）是一种新的模式，通过提供低辐射剂量的三维（3D）成像，有可能提高乳腺癌的早期检测。3D图像重建提出了一些挑战：锥束和平板几何形状，以及高度不完整的采样。克服这些挑战的一个有前途的手段是统计迭代重建（IR），因为它提供了准确的物理建模和系统几何形状的一般描述的灵活性。作者的目标是开发将统计IR应用于断层合成成像数据的技术。方法采用基于局部体素对的先验物理模型，通过灵活的参数调整图像质量，在先验中预先计算参数λ，消除数据依赖性，获得均匀的分辨率特性，采用有效的射线驱动技术计算前向和后向投影，利用前向投影和后向投影计算图像质量。以及过采样、射线驱动的方法，以利用实际的感兴趣区域技术来执行高分辨率重建。为了评估这些技术的性能，作者在固定DBT原型系统上采集了体模数据。为了解决估计问题，作者提出了一种基于优化传递的算法框架，该框架可能允许更少的迭代来实现可接受的收敛重建。结果红外成像提高了低对比度和微小钙化点的检出率，减少了交叉伪影，提高了空间分辨率，降低了重建图像的噪声。结论：尽管计算负荷仍然是实际开发的一个重大挑战，但统计IR提供的上级图像质量与先进的计算技术相结合，可能会为临床应用中的筛查、诊断和术中成像带来益处。
PURPOSE Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means of overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors' goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. METHODS These techniques include the following: a physics model with a local voxel-pair based prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. RESULTS IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. CONCLUSIONS Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications.