Angelis Georgios I, Kotasidis Fotis A, Matthews Julian C, Markiewicz Pawel J, Lionheart William R, Reader Andrew J
Faculty of Health Sciences and Brain and Mind Research Institute, The University of Sydney, Sydney, NSW 2006, Australia.
Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, University of Geneva, Geneva, Switzerland.
Phys Med. 2015 Mar;31(2):137-45. doi: 10.1016/j.ejmp.2014.12.008. Epub 2015 Jan 14.
Accurate characterisation of the scanner's point spread function across the entire field of view (FOV) is crucial in order to account for spatially dependent factors that degrade the resolution of the reconstructed images. The HRRT users' community resolution modelling reconstruction software includes a shift-invariant resolution kernel, which leads to transaxially non-uniform resolution in the reconstructed images. Unlike previous work to date in this field, this work is the first to model the spatially variant resolution across the entire FOV of the HRRT, which is the highest resolution human brain PET scanner in the world. In this paper we developed a spatially variant image-based resolution modelling reconstruction dedicated to the HRRT, using an experimentally measured shift-variant resolution kernel. Previously, the system response was measured and characterised in detail across the entire FOV of the HRRT, using a printed point source array. The newly developed resolution modelling reconstruction was applied on measured phantom, as well as clinical data and was compared against the HRRT users' community resolution modelling reconstruction, which is currently in use. Results demonstrated improvements both in contrast and resolution recovery, particularly for regions close to the edges of the FOV, with almost uniform resolution recovery across the entire transverse FOV. In addition, because the newly measured resolution kernel is slightly broader with wider tails, compared to the deliberately conservative kernel employed in the HRRT users' community software, the reconstructed images appear to have not only improved contrast recovery (up to 20% for small regions), but also better noise characteristics.
准确表征扫描仪在整个视野（FOV）内的点扩散函数，对于考虑那些会降低重建图像分辨率的空间相关因素至关重要。HRRT用户社区分辨率建模重建软件包含一个平移不变分辨率内核，这会导致重建图像在横轴方向上分辨率不均匀。与该领域此前的工作不同，本研究首次对HRRT整个视野内的空间可变分辨率进行建模，HRRT是世界上分辨率最高的人脑PET扫描仪。在本文中，我们利用实验测量得到的平移可变分辨率内核，开发了一种专门用于HRRT的基于空间可变图像的分辨率建模重建方法。此前，使用打印点源阵列在HRRT的整个视野内对系统响应进行了详细测量和表征。将新开发的分辨率建模重建方法应用于测量的体模以及临床数据，并与目前正在使用的HRRT用户社区分辨率建模重建方法进行比较。结果表明，在对比度和分辨率恢复方面均有改善，特别是在靠近视野边缘的区域，在整个横向视野内分辨率恢复几乎均匀。此外，由于新测量的分辨率内核与HRRT用户社区软件中使用的刻意保守内核相比，略宽且尾部更宽，重建图像不仅对比度恢复得到改善（小区域可达20%），而且噪声特性更好。
