Feng Ziwei, Hooshangnejad Hamed, Shin Eun Ji, Narang Amol, Lediju Bell Muyinatu A, Ding Kai
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States.
Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Front Oncol. 2021 Nov 4;11:759811. doi: 10.3389/fonc.2021.759811. eCollection 2021.
We proposed a Haar feature-based method for tracking endoscopic ultrasound (EUS) probe in diagnostic computed tomography (CT) and Magnetic Resonance Imaging (MRI) scans for guiding hydrogel injection without external tracking hardware. This study aimed to assess the feasibility of implementing our method with phantom and patient images.
Our methods included the pre-simulation section and Haar features extraction steps. Firstly, the simulated EUS set was generated based on anatomic information of interpolated CT/MRI images. Secondly, the efficient Haar features were extracted from simulated EUS images to create a Haar feature dictionary. The relative EUS probe position was estimated by searching the best matched Haar feature vector of the dictionary with Haar feature vector of target EUS images. The utilization of this method was validated using EUS phantom and patient CT/MRI images.
In the phantom experiment, we showed that our Haar feature-based EUS probe tracking method can find the best matched simulated EUS image from a simulated EUS dictionary which includes 123 simulated images. The errors of all four target points between the real EUS image and the best matched EUS images were within 1 mm. In the patient CT/MRI scans, the best matched simulated EUS image was selected by our method accurately, thereby confirming the probe location. However, when applying our method in MRI images, our method is not always robust due to the low image resolution.
Our Haar feature-based method is capable to find the best matched simulated EUS image from the dictionary. We demonstrated the feasibility of our method for tracking EUS probe without external tracking hardware, thereby guiding the hydrogel injection between the head of the pancreas and duodenum.
我们提出了一种基于哈尔特征的方法,用于在诊断性计算机断层扫描(CT)和磁共振成像(MRI)扫描中跟踪内镜超声(EUS)探头,以在无需外部跟踪硬件的情况下引导水凝胶注射。本研究旨在评估使用体模和患者图像实施我们方法的可行性。
我们的方法包括预模拟部分和哈尔特征提取步骤。首先,基于插值CT/MRI图像的解剖信息生成模拟EUS集。其次,从模拟EUS图像中提取有效的哈尔特征以创建哈尔特征字典。通过将字典中最佳匹配的哈尔特征向量与目标EUS图像的哈尔特征向量进行搜索,估计EUS探头的相对位置。使用EUS体模和患者CT/MRI图像验证了该方法的实用性。
在体模实验中,我们表明基于哈尔特征的EUS探头跟踪方法可以从包含123幅模拟图像的模拟EUS字典中找到最佳匹配的模拟EUS图像。真实EUS图像与最佳匹配EUS图像之间所有四个目标点的误差均在1毫米以内。在患者CT/MRI扫描中,我们的方法准确地选择了最佳匹配的模拟EUS图像,从而确定了探头位置。然而,当在MRI图像中应用我们的方法时,由于图像分辨率低,该方法并不总是稳健的。
我们基于哈尔特征的方法能够从字典中找到最佳匹配的模拟EUS图像。我们证明了在无需外部跟踪硬件的情况下跟踪EUS探头的方法的可行性,从而指导在胰腺头部和十二指肠之间进行水凝胶注射。