Department of Joint Surgery @ 1st Affiliated Hospital of Guangzhou Medical College & Orthopedic implantation key lab of Guangdong Province, China.
Eur J Radiol. 2012 Mar;81(3):e406-13. doi: 10.1016/j.ejrad.2011.12.031. Epub 2012 Jan 18.
To investigate a registration approach for 2-dimension (2D) based on characteristic localization to achieve 3-dimension (3D) fusion from images of PET, CT and MR one by one.
A cubic oriented scheme of"9-point & 3-plane" for co-registration design was verified to be geometrically practical. After acquisiting DICOM data of PET/CT/MR (directed by radiotracer 18F-FDG etc.), through 3D reconstruction and virtual dissection, human internal feature points were sorted to combine with preselected external feature points for matching process. By following the procedure of feature extraction and image mapping, "picking points to form planes" and "picking planes for segmentation" were executed. Eventually, image fusion was implemented at real-time workstation mimics based on auto-fuse techniques so called "information exchange" and "signal overlay".
The 2D and 3D images fused across modalities of [CT+MR], [PET+MR], [PET+CT] and [PET+CT+MR] were tested on data of patients suffered from tumors. Complementary 2D/3D images simultaneously presenting metabolic activities and anatomic structures were created with detectable-rate of 70%, 56%, 54% (or 98%) and 44% with no significant difference for each in statistics.
Currently, based on the condition that there is no complete hybrid detector integrated of triple-module [PET+CT+MR] internationally, this sort of multiple modality fusion is doubtlessly an essential complement for the existing function of single modality imaging.
研究一种基于特征定位的二维(2D)配准方法,以实现从 PET、CT 和 MR 图像逐个实现三维(3D)融合。
验证了一种用于共配准设计的立方定向“9 点和 3 平面”方案在几何上是可行的。在获取 PET/CT/MR 的 DICOM 数据(由放射性示踪剂 18F-FDG 等引导)后,通过 3D 重建和虚拟解剖,对人体内部特征点进行排序,然后与预选的外部特征点进行匹配。按照特征提取和图像映射的步骤,执行“选点成面”和“选面分割”。最终,在基于自动融合技术的实时工作站模拟中实现图像融合,即所谓的“信息交换”和“信号叠加”。
在对肿瘤患者的数据进行测试时,成功实现了 [CT+MR]、[PET+MR]、[PET+CT] 和 [PET+CT+MR] 等多种模态的 2D 和 3D 图像融合。同时呈现代谢活动和解剖结构的互补 2D/3D 图像的创建率分别为 70%、56%、54%(或 98%)和 44%,在统计学上没有显著差异。
目前,在国际上还没有完全集成三模块 [PET+CT+MR] 的混合探测器的情况下,这种多模态融合无疑是对现有单模态成像功能的重要补充。