Lai Yi-Chen, Ray Kimberly M, Mainprize James G, Kelil Tatiana, Joe Bonnie N
National Yang-Ming University, School of Medicine, Taipei, Taiwan.
Taipei Veterans General Hospital, Department of Radiology, Taipei, Taiwan.
J Breast Imaging. 2020 Nov 21;2(6):615-628. doi: 10.1093/jbi/wbaa086.
Image optimization at digital breast tomosynthesis (DBT) involves a series of trade-offs between multiple variables. Wider sweep angles provide better separation of overlapping tissues, but they result in decreased in-plane resolution as well as increased scan times that may be prone to patient motion. Techniques to reduce scan time, such as continuous tube motion and pixel binning during detector readout, reduce the chances of patient motion but may degrade the in-plane resolution. Image artifacts are inherent to DBT because of the limited angular range of the acquisition. Iterative reconstruction algorithms have been shown to reduce various DBT artifacts.
数字乳腺断层合成(DBT)中的图像优化涉及多个变量之间的一系列权衡。更宽的扫描角度能更好地分离重叠组织,但会导致平面内分辨率降低以及扫描时间增加,而扫描时间增加可能会使患者更容易出现移动。减少扫描时间的技术,如探测器读出期间的连续管运动和像素合并,可降低患者移动的几率,但可能会降低平面内分辨率。由于采集的角度范围有限,图像伪影是DBT固有的。迭代重建算法已被证明可以减少各种DBT伪影。