Foroughi Pezhman, Abolmaesumi Purang, Hashtrudi-Zaad Keyvan
Department of Electrical and Computer Engineering, Queen's University, Canada.
Med Image Anal. 2006 Oct;10(5):713-25. doi: 10.1016/j.media.2006.06.008. Epub 2006 Aug 14.
3D registration of ultrasound images is an important and fast-growing research area with various medical applications, such as image-guided radiotherapy and surgery. However, this registration process remains extremely challenging due to the deformation of soft tissue and the existence of speckles in these images. This paper presents a technique for intra-subject, intra-modality elastic registration of 3D ultrasound images. Using the general concept of attribute vectors, we define the corresponding voxels in the fixed and moving images. Our method does not require presegmentation and does not employ any numerical optimization procedure. As the computational requirements are minimal, the method has potential use in real-time applications. The technique is implemented and tested on 3D ultrasound images of human liver, captured by a 3D ultrasound transducer. The results show that the method is sufficiently accurate and robust even in cases where artifacts such as shadows exist in the ultrasound data.
超声图像的三维配准是一个重要且快速发展的研究领域,具有多种医学应用,如图像引导放疗和手术。然而,由于软组织的变形以及这些图像中斑点的存在,这种配准过程仍然极具挑战性。本文提出了一种用于三维超声图像的受试者内、模态内弹性配准技术。利用属性向量的一般概念,我们定义了固定图像和移动图像中的相应体素。我们的方法不需要预分割,也不采用任何数值优化程序。由于计算需求最小,该方法在实时应用中具有潜在用途。该技术在由三维超声换能器采集的人体肝脏三维超声图像上进行了实现和测试。结果表明,即使在超声数据中存在阴影等伪影的情况下,该方法也具有足够的准确性和鲁棒性。