Deep brain stimulation (DBS) surgery is an important treatment for patients with Parkinson's disease in the middle and late stages. The accuracy of the implantation of electrode at the location of the nuclei directly determines the therapeutic effect of the operation. At present, there is no single imaging method that can obtain images with electrodes, nuclei and their positional relationship. In addition, the subthalamic nucleus is small in size and the boundary is not obvious, so it cannot be directly segmented. In this paper, a complete end-to-end DBS effect evaluation pipeline was constructed using magnetic resonance (MR) data of T1, T2 and SWI weighted by DBS surgery. Firstly, the images of preoperative and postoperative patients are registered and normalized to the same coordinate space. Secondly, the patient map is obtained by non-rigid registration of brain map and preoperative data, as well as the preoperative nuclear cluster prediction position. Then, a three-dimensional (3D) image of the positional relationship between the electrode and the nucleus is obtained by using the electrode path in the postoperative image and the result of the nuclear segmentation. The 3D image is helpful for the evaluation of the postoperative effect of DBS and provides effective information for postoperative program control. After analysis, the algorithm can achieve a good registration between the patient's DBS surgical image and the brain map. The error between the algorithm and the expert evaluation of the physical coordinates of the center of the thalamus is (1.590 ± 1.063) mm. The problem of postoperative evaluation of the placement of DBS surgical electrodes is solved.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929959PMC
http://dx.doi.org/10.7507/1001-5515.201711055DOI Listing

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