成像体模
支气管镜检查
跟踪(教育)
迭代最近点
期望最大化算法
混合模型
职位(财务)
方向(向量空间)
计算机科学
计算机视觉
高斯分布
特征(语言学)
人工智能
数学
放射科
模式识别(心理学)
医学
点云
最大似然
统计
物理
几何学
语言学
哲学
经济
量子力学
教育学
心理学
财务
作者
Saeedeh Navaei Lavasani,Parastoo Farnia,Ebrahim Najafzadeh,Samaneh Saghatchi,Mehdi Samavati,Hamidreza Abtahi,MohammadReza Deevband,Alireza Ahmadian
标识
DOI:10.1088/1361-6560/abca07
摘要
Electromagnetic-based navigation bronchoscopy requires accurate and robust estimation of the bronchoscope position inside the bronchial tree. However, respiratory motion, coughing, patient movement, and airway deformation inflicted by bronchoscope significantly hinder the accuracy of intraoperative bronchoscopic localization. In this study, a real-time and automatic registration procedure was proposed to superimpose the current location of the bronchoscope to corresponding locations on a centerline extracted from bronchial computed tomography (CT) images. A centerline-guided Gaussian mixture model (CG-GMM) was introduced to register a bronchoscope's position concerning extracted centerlines. A GMM was fitted to bronchoscope positions where the orientation likelihood was chosen to assign the membership probabilities of the mixture model, which led to preserving the global and local structures. The problem was formulated and solved under the expectation maximization framework, where the feature correspondence and spatial transformation are estimated iteratively. Validation was performed on a dynamic phantom with four different respiratory motions and four human real bronchoscopy (RB) datasets. Results of the experiments conducted on the bronchial phantom showed that the average positional tracking error using the proposed approach was equal to 1.98 [Formula: see text] 0.98 mm that was reduced in comparison with independent electromagnetic tracking (EMT), iterative closest point (ICP), and coherent point drift (CPD) methods by 64%, 58%, and 53%, respectively. In the patient assessment part of the study, the average positional tracking error was 4.73 [Formula: see text] 4.76 mm and compared to ICP, and CPD methods showed 31.4% improvement of successfully tracked frames. Our approach introduces a novel method for real-time respiratory motion compensation that provides reliable guidance during bronchoscopic interventions and, thus could increase the diagnostic yield of transbronchial biopsy.
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