Woo Jonghye, Slomka Piotr J, Dey Damini, Cheng Victor, Ramesh Amit, Hong Byung-Woo, Jay Kuo C-C, Berman Daniel S, Germano Guido
University of Southern California, Los Angeles, CA 90089-2564, USA ; Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Proc IEEE Int Symp Biomed Imaging. 2009:358-361. doi: 10.1109/ISBI.2009.5193058.
A multi-modality image registration algorithm for the alignment of myocardial perfusion SPECT (MPS) and coronary computed tomography angiography (CTA) scans is presented in this work. Coronary CTA and MPS provides clinically complementary information in the diagnosis of coronary artery disease. An automated registration algorithm is proposed utilizing segmentation results of MPS volumes, where regions of myocardium and blood pools are extracted and used as an anatomical mask. Using a variational framework, we adopt an energy functional with a piecewise constant image model and optimize it numerically with a gradient descent algorithm. The computational efficiency and robustness of the proposed automatic registration of CTA with MPS have been demonstrated by the experiments that yielded an average error smaller than an MPS voxel size.
本文提出了一种用于心肌灌注单光子发射计算机断层扫描（MPS）与冠状动脉计算机断层血管造影（CTA）扫描对齐的多模态图像配准算法。冠状动脉CTA和MPS在冠状动脉疾病诊断中提供临床互补信息。提出了一种利用MPS体积分割结果的自动配准算法，其中提取心肌和血池区域并用作解剖掩码。使用变分框架，我们采用具有分段常数图像模型的能量泛函，并使用梯度下降算法对其进行数值优化。通过实验证明了所提出的CTA与MPS自动配准的计算效率和鲁棒性，实验产生的平均误差小于MPS体素大小。
