Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information
Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information
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DOI：
10.1088/0031-9155/56/1/008
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发表时间：
2011-01-07
影响因子：
3.5
通讯作者：
Ra, Jong Beom
中科院分区：
文献类型：
--
作者：
Lee, Duhgoon;Nam, Woo Hyun;Ra, Jong Beom
为了将肝脏的超声（US）和计算机断层摄影（CT）图像同时用于诸如诊断和图像引导的介入的医学应用，这两种类型的图像之间的非刚性配准是必要的步骤，因为由于所涉及的不同呼吸相位以及由于在US成像中发生的探头压力而存在US和CT图像之间的局部变形。介绍了一种基于体素的肝脏三维B超图像与CT图像的非刚性配准算法。在该算法中，为了提高配准精度，我们利用的表面信息的肝脏和胆囊除了肝脏内部的血管信息。为了在US和CT图像之间进行有效的相关性，我们根据US和CT图像中的解剖区域的特征分别处理这些解剖区域。该方法基于一种新的目标函数，利用三维灰度和梯度联合直方图信息，依次进行基于血管的非刚性配准和基于表面的非刚性配准，提高了配准精度。所提出的算法进行了测试，为10个临床数据集和定量评价进行。实验结果表明，即使存在因呼吸时相和探头压力不同而造成的局部变形，超声和CT图像解剖特征之间的配准误差平均小于2 mm。此外，病变配准误差平均小于3 mm，最大4.5 mm被认为对于临床应用是可接受的。
In order to utilize both ultrasound (US) and computed tomography (CT) images of the liver concurrently for medical applications such as diagnosis and image-guided intervention, non-rigid registration between these two types of images is an essential step, as local deformation between US and CT images exists due to the different respiratory phases involved and due to the probe pressure that occurs in US imaging. This paper introduces a voxel-based non-rigid registration algorithm between the 3D B-mode US and CT images of the liver. In the proposed algorithm, to improve the registration accuracy, we utilize the surface information of the liver and gallbladder in addition to the information of the vessels inside the liver. For an effective correlation between US and CT images, we treat those anatomical regions separately according to their characteristics in US and CT images. Based on a novel objective function using a 3D joint histogram of the intensity and gradient information, vessel-based non-rigid registration is followed by surface-based non-rigid registration in sequence, which improves the registration accuracy. The proposed algorithm is tested for ten clinical datasets and quantitative evaluations are conducted. Experimental results show that the registration error between anatomical features of US and CT images is less than 2 mm on average, even with local deformation due to different respiratory phases and probe pressure. In addition, the lesion registration error is less than 3 mm on average with a maximum of 4.5 mm that is considered acceptable for clinical applications.