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首页> 外文会议>Physics of Medical Imaging pt.3; Progress in Biomedical Optics and Imaging; vol.7 no.28 >Implementing an iterative reconstruction algorithm for digital breast tomosynthesis on graphics processing hardware
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Implementing an iterative reconstruction algorithm for digital breast tomosynthesis on graphics processing hardware

机译：在图形处理硬件上实现数字乳房断层合成的迭代重建算法

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摘要

The Maximum Likelihood Expectation Maximization (MLEM) algorithm has been shown to produce the highest quality Digital Breast Tomosynthesis (DBT) images. MLEM, however, is computationally intensive. Single-processor image reconstruction times for each breast were on the order of several hours. In order for DBT to be clinically useful, faster reconstruction times using cost-effective software/hardware solutions are needed. We have implemented the MLEM reconstruction algorithm for use with DBT on a graphics processing unit (GPU). Compared to a single optimized 2.8GHz Pentium system this enabled a 113-fold speedup in processing time, while maintaining high image quality. Subsequently, we added various additional processing steps to the reconstruction algorithm in order to improve image quality and diagnostic properties. Since the performance of commercial GPUs increases rapidly, with little change in cost, the increased sophistication in processing does not entail an increase in system cost. The use of GPUs for reconstruction represents a technical breakthrough in the cost-effective application of MLEM to Digital Breast Tomosynthesis.
机译：最大似然期望最大化（MLEM）算法已显示出可产生最高质量的数字乳房断层合成（DBT）图像。但是，MLEM是计算密集型的。每个乳房的单处理器图像重建时间约为几个小时。为了使DBT在临床上有用，需要使用经济高效的软件/硬件解决方案加快重建时间。我们已经在图形处理单元（GPU）上实现了与DBT一起使用的MLEM重建算法。与单个优化的2.8GHz Pentium系统相比，这可以使处理时间加快113倍，同时保持高图像质量。随后，我们将各种其他处理步骤添加到了重建算法中，以提高图像质量和诊断性能。由于商用GPU的性能迅速提高，而成本却几乎没有变化，因此处理的复杂性提高并不会导致系统成本的增加。使用GPU进行重建代表了MLEM在数字乳房断层合成中的经济有效应用中的技术突破。

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