图像配准
初始化
计算机科学
人工智能
计算机视觉
图像(数学)
程序设计语言
作者
Fadil Al-Jaberi,Matthias Moeskes,Martin Skalej,Melanie Fachet,Christoph Hoeschen
出处
期刊:Brain Sciences
[Multidisciplinary Digital Publishing Institute]
日期:2025-05-19
卷期号:15 (5): 521-521
标识
DOI:10.3390/brainsci15050521
摘要
Objectives: This study aimed to develop a semi-automated registration method for aligning preoperative non-contrast T2-weighted MRI with postoperative high-resolution cone-beam CT (DynaCT) in patients undergoing directional deep brain stimulation (dDBS) surgery targeting the subthalamic nucleus (STN). The aim was to facilitate image-guided programming of DBS devices and postoperative verification of the alignment of segmented contacts. Materials and Methods: A dataset of ten patients undergoing bilateral dDBS implantation was retrospectively collected, including DynaCT (acquired postoperatively) and non-contrast T2-weighted MRI (obtained preoperatively). A semi-automated registration method was used, employing manual initialization due to dissimilar anatomical information between DynaCT and T2-weighted MRI. Image visualization, initial alignment using a centered transformation initializer, and single-resolution image registration involving the Simple Insight Toolkit (SimpleITK) library were performed. Manual landmark-based alignment based on anatomical landmarks and evaluation metrics such as Target Registration Error (TRE) assessed alignment accuracy. Results: The registration method successfully aligned all images. Quantitative evaluation revealed an average of the mean TRE of 1.48 mm across all subjects, indicating satisfactory alignment quality. Multiplanar reformations (MPRs) based on electrode-oriented normal vectors visualized segmented contacts for accurate electrode placement. Conclusions: The developed method demonstrated successful registration between preoperative non-contrast T2-weighted MRI and postoperative DynaCT, despite dissimilar anatomical information. This approach facilitates accurate alignment crucial for DBS programming and postoperative verification, potentially reducing the programming time of the DBS. The study underscores the importance of image quality, manual initialization and semi-automated registration methods for successful multimodal image registration in dDBS procedures targeting the STN.
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