标题：Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT
作者：Liu, Qingyi; Mohy-ud-Din, Hassan; Boutagy, Nabil E.; Jiang, Mingyan; Ren, Silin; Stendahl, John C.; Sinusas, Albert J.; Liu, Chi
作者机构：[Liu, Qingyi; Jiang, Mingyan] Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Shandong, Peoples R China.; [Liu, Qingyi; Mohy-ud-Din, Hassan; S 更多
通讯作者地址：[Liu, C]Yale Univ, Dept Radiol & Biomed Imaging, New Haven, CT 06520 USA;[Liu, C]Yale Univ, Dept Biomed Engn, New Haven, CT 06520 USA.
来源：PHYSICS IN MEDICINE AND BIOLOGY
关键词：multi-atlas based segmentation; partial volume correction; cardiac; SPECT/CT
摘要：Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine Tc-99m-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.