Implementation of Image Reconstruction for GE SIGNA PET/MR PET Data in the STIR Library
Implementation of Image Reconstruction for GE SIGNA PET/MR PET Data in the STIR Library
复制标题
STIR 库中 GE SIGNA PET/MR PET 数据图像重建的实现
DOI：
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发表时间：
2018
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通讯作者：
C. Tsoumpas
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作者：
Palak Wadhwa;K. Thielemans;Nikos Efthimiou;Ottavia Bertolli;Elise Emond;B. Thomas;M. Tohme;K. Wangerin;G. Delso;W. Hallett;R. Gunn;D. Buckley;C. Tsoumpas
断层扫描图像重建软件(STIR：http://stir.sf.net))是一个开源的C++库，可用于重建发射断层扫描数据。这项工作旨在将GE SIGNA PET/MR扫描仪整合到STIR中，并实现带数据校正的PET图像重建。采集后从扫描仪提取的数据包括原始数据文件(发射、归一化、几何和井计数器校准(WCC)因素)、磁共振衰减校正(MRAC)图像和基于扫描仪的重建的列表。LISTMODE(LM)文件存储了每秒每个晶体的提示事件和单曲的列表。来自扫描仪的MRAC图像用于衰减校正。还描述了对STIR的修改，以允许在与扫描仪相同的正弦图组织中对该LM数据进行准确的直方图绘制。这允许使用STIR重建具有所有数据校正的采集数据，并且独立于制造商提供的任何软件。通过将使用有序子集期望最大化(OSEM)算法的直方图数据、数据校正和最终重建与制造商为扫描仪提供的GE工具箱中的等价物进行比较，验证了实施方案。直方图计数无差异，归一化和随机校正的总相对差异分别为6.7×10−8%和0.0 1%~0.86%。STIR重建图像具有相似的分辨率和量化，但由于WCC因素、衰变和死区时间校正以及PET和MR门架之间的偏移，存在一些残留差异，这将在未来的工作中解决。这项工作将允许使用所有当前和未来的STIR算法，包括惩罚图像重建、运动校正和直接参数图像估计，来自GE SIGNA PET/MR扫描仪的数据。
Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) is an open source C++ library available for reconstruction of emission tomography data. This work aims at the incorporation of the GE SIGNA PET/MR scanner in STIR and enables PET image reconstruction with data corrections. The data extracted from the scanner after an acquisition includes a list of raw data files (emission, normalisation, geometric and well counter calibration (wcc) factors), magnetic resonance attenuation correction (MRAC) images and the scanner-based reconstructions. The listmode (LM) file stores a list of ’prompt’ events and the singles per crystal per second. MRAC images from the scanner are used for attenuation correction. The modifications to STIR that allow accurate histogramming of this LM data in the same sinogram organisation as the scanner are also described. This allows reconstruction of acquisition data with all data corrections using STIR, and independent of any software supplied by the manufacturer. The implementations were validated by comparing the histogrammed data, data corrections and final reconstruction using the ordered subset expectation maximisation (OSEM) algorithm with the equivalents from the GE-toolbox, supplied by the manufacturer for the scanner. There is no difference in the histogrammed counts whereas an overall relative difference of 6.7 × 10−8% and from 0.01% to 0.86% is seen in the normalisation and randoms correction sinograms respectively. The STIR reconstructed images have similar resolution and quantification but have some residual differences due to wcc factors, decay and deadtime corrections, as well as the offset between PET and MR gantries that will be addressed in future work. This work will enable the use of all current and future STIR algorithms, including penalized image reconstruction, motion correction and direct parametric image estimation, on data from GE SIGNA PET/MR scanners.