形变块匹配跟踪(1)：配准跟踪与几何约束_bg

编程入门行业动态更新时间:2024-10-17 09:37:56

参看论文：Fast and robust 3D ultrasound registration – Block and game theoretic matching

期刊水平：Medical imaging analysis (MIA)

投稿单位：伊拉斯谟医学院计算医学中心

文章作者设计了一种全局稠密块匹配的跟踪算法，原理是序列配准，核心是几何约束下的outliers reject策略。

1. 摘要

Real-time 3D US has potential for image guidance in minimally invasive liver interventions. However, motion caused by patient breathing makes it hard to visualize a localized area, and to maintain alignment with pre-operative information. In this work we develop a fast affine registration framework to compensate in real-time for liver motion/displacement due to breathing. The affine registration of two consecutive ultrasound volumes in time is performed using block-matching. For a set of evenly distributed points in one volume and their correspondences in the other volume, we propose a robust outlier rejection method to reject false matches. The inliers are then used to determine the affine transformation. The approach is evaluated on 13 4D ultrasound sequences acquired from 8 subjects. For 91 pairs of 3D ultrasound volumes selected from these sequences, a mean registration error of 1.8 mm is achieved. A graphics processing unit (GPU) implementation runs the 3D US registration at 8 Hz.

在微创肝脏介入治疗中，实时的3D超声有潜力成为影像导航工具。然而，由于患者呼吸引发的运动使得观察一个固定点、并与术前的信息匹配变得很难。该工作中，作者开发了一个快速的彷射框架实时的补偿由于呼吸运动引发的肝脏运动偏移。两个连续的3D立体之间的的彷射配准是通过块匹配完成的。对于两个3D立体中均匀分布的点集，作者提出了一种鲁棒性的离群排斥方法，拒绝错误的匹配信息。inliers（也就是正确的匹配信息）被用于确定仿射变换矩阵。作者从8位受试者中采集到了13个超声序列，从这些序列中选择了91对3D立体，实现了1.8mm的配准误差。此外，作者还采用了GPU对3D超声之间的配准进行加速，最终实现了8Hz的速度。

2. 背景

1.1 临床动机

Replacing classical surgical interventions by minimally invasive alternatives is beneficial for the patient and the health care system, as it has large potential for reducing complication rates, minimizing surgical trauma, and reducing hospital stay. The minimally invasive character, however, makes these interventions challenging for the clinician. There is no direct eyesight on the target region and conventional interventional imaging modalities have limited capabilities. Furthermore the user interfacing and interaction with the equipment involved often is not ergonomically well-designed, and does not match the interventional work flow well. Image guidance is crucial in minimally invasive interventions. Image guidance can be based on preoperative imaging data (mostly magnetic resonance imaging and computed tomography) or intraoperative imaging data (X-ray, ultrasound). Hybrid approaches can also be useful, in which the diagnostic quality of preoperative images can be combined with the real-time nature of intraoperative images (also known as fusion imaging). Four dimensional (4D) ultrasound (US) is a relatively novel imaging modality that currently is mainly used for diagnosis.
用微创取代传统的手术干预对患者和健康监护系统非常有利，因为微创手术可以降低病症的发生率、最小化手术创伤和减少住院时间。然而，由于微创手术本身的原因，使得这种介入方式在临床上面临挑战。医生并不能看见目标区域，传统的介入成像模式更是能力有限。此外，用于介入手术治疗的器械也与手术流程不相匹配。图像导航在微创介入手术中非常重要。图像导航可以基于术前的图像数据（主要是MR和CT）以及术中影像数据（X-ray，超声）。混合影像的方法也是非常有用的，将术前影像和术中影像联合使用（就是图像配准+图像融合）。4D超声是一种非常新的成像模态，当前主要用于诊断中。

Radiofrequency ablation (RFA) and the transjugular intrahepatic portosystemic shunt (TIPS) procedure are examples of percutaneous minimally invasive image-guided interventions which are used more and more as alternative to surgical procedures. 4D US has large potential in assisting the clinicians in these procedures, as it provides real-time three dimensional (3D) vision. During these procedures the clinician often holds the US probe steady to visualize a localized area in the liver US volume. Breathing shifts the region of interest and makes it difficult to constantly focus on a region of interest, more so in the presence of a catheter. The purpose of our work is to develop a technique suited for fast 3D ultrasound registration during image guided minimally invasive intervention to compensate breathing motion. In addition, our approach would help in keeping the registration up to date in US fusion imaging.

1.2 相关工作

理解一下图像配准技术：

Image registration is the process of aligning two or more frames of the same or similar scene. The basic input data to the
registration process are two images: the fixed image and the moving image.These approaches are either feature-based
or intensity-based. Intensity-based methods compare intensity patterns in images via similarity metrics, registering either images or sub images. If sub images are registered, centers of corresponding sub images are treated as corresponding feature points. 图像配准是指对齐两个或多个具有相同或相似的场景的帧。配准过程需要输入两张图像，参考图像和移动图像。这一类方法可以分为基于特征和基于灰度的配准方法。基于灰度的方法需要通过相似性度量计算两个图像灰度模式之间的距离。配准可以再图像和图像子块之间进行。

相似性度量

误差平方和 Sum of Square Different SSD; 绝对误差和 Sum of absolut Different, SAD; 归一化互相关 Normalization Cross-correlation. 互信息 Mutual Information, MI.

互信息提出文献：Mattes, D., Haynor, D.R., Vesselle, H., Lewellyn, T.K., Eubank, W., 2001. Nonrigid multimodality image registration, pp. 1609–1620. http://dx.doi/10.1117/12.431046.

互信息最适合用于US-US配准：Kaar, M., Figl, M., Hoffmann, R., Birkfellner, W., Hummel, J., Stock, M., Georg, D., Goldner, G., 2013. Automatic patient alignment system using 3D ultrasound. Med. Phys. 40. http://dx.doi/10.1118/1.4795129.

Vijayan研究了4D超声序列离线分段配准的工作：Vijayan, S., Klein, S., Hofstad, E., Lindseth, F., Ystgaard, B., Lang, T., 2013. Validation of a non-rigid registration method for motion compensation in 4D ultrasound of the liver. In: IEEE ISBI2013. Work done in collaboration with NTNU/SINTEF, Trondheim, Norway.

特征描述

基于属性向量：Foroughi, P., Abolmaesumi, P., Hashtrudi-Zaad, K., 2006. Intra-subject elastic registration of 3D ultrasound images. Med. Image Anal. 10, 713–725.

基于信息论的特征描述子：Wang, Z.W., Slabaugh, G.G., Unal, G.B., Fang, T., 2007. Registration of ultrasound images using an information-theoretic feature detector. In: ISBI, pp. 736–739.

3D SIFT描述子：

Ni, D., Chui, Y.P., Qu, Y., Yang, X.S., Qin, J., Wong, T.T., Ho, S.S.H., Heng, P.A., 2009. Reconstruction of volumetric ultrasound panorama based on improved 3D sift. Comp. Med. Imag. Graph. 33, 559–566.

Skibbe, H., Reisert, M., Schmidt, T., Brox, T., Ronneberger, O., Burkhardt, H., 2012. Fast rotation invariant 3D feature computation utilizing efficient local neighborhood operators. IEEE Trans. Pattern Anal. Mach. Intell. 34, 1563–1575.

局部相位描述子：Grau, V., Becher, H., Noble, J.A., 2007. Registration of multiview real-time 3-D echocardiographic sequences. IEEE Trans. Med. Imag. 26, 1154–1165.
基于混合特征配准：Cifor, A., Risser, L., Chung, D., Anderson, E., Schnabel, J., 2013. Hybrid feature-based diffeomorphic registration for tumor tracking in 2-D liver ultrasound images. IEEE Trans. Med. Imag. 32, 1647–1656. http://dx.doi/10.1109/ TMI.2013.2262055.

在最近几年基于灰度强度的配准方法在所有的基于特征配准里面是最火的。作者认为，从信息论角度来看，只要是特征提取就一定会存在信息损失。但是，如果考虑到数据噪声比较严重或者目标发生了形变，开发抵抗这种不变性的特征描述子还是非常重要的。有效的特征可以提升不同目标的判别能力，同时降低数据的维度。目前也存在一些实时3D-3D配准的工作。

基于小波特征的多视角融合：Rajpoot, K., Noble, J.A., Grau, V., Szmigielski, C., Becher, H., 2009. Multiview RT3D echocardiography image fusion. In: FIMH, pp. 134–143.

SSD+灰度特征：Øye, O.K., Wein, W., Ulvang, D.M., Matre, K., Viola, I., 2012. Real time image-based tracking of 4D ultrasound data. In: MICCAI (1), pp. 447–454.

特征对齐：Schneider, R.J., Perrin, D.P., Vasilyev, N.V., Marx, G.R., del Nido, P.J., Howe, R.D., 2012. Real-time image-based rigid registration of three-dimensional ultrasound. Med. Image Anal. 16, 402–414.

2.3 灵感来源及贡献

Our ultrasound registration approach is motivated by methods described in ultrasound speckle tracking literature, see Harris et al. (2010). A speckle pattern contains densely positioned targets created by the interaction of ultrasonic beams and the tissue.
In an ideal scenario, if all the speckle patterns are tracked accurately, the speckle pattern correspondences can be used to estimate the transformation. However in practice not all of the speckle patterns will be tracked well, e.g. because of acoustic shadowing or due to motion decorrelation。

在理想环境中，如果斑点模式可以准确的被跟踪，我们可以利用斑点间的相关性直接进行变换矩阵估计。然而，在实际中，并不是所有的斑点都可以很好的跟踪，特别是在声影和运动去相关环境下。

Liang, T., Yung, L.S., Yu, W., 2013. On feature motion decorrelation in ultrasound speckle tracking. IEEE Trans. Med. Imag. 32, 435–448.

To address these issues and to remove false matches, we employ a matching approach, inspired by game theory, to retain only pairs that have been matched correctly. This outlier rejection is formulated in a game theoretic framework. Speed is an important aspect of our application, and a matching strategy reduces over reliance on selecting the speckle patterns.

为了解决这个问题（去掉由于声影和运动去相关造成的误匹配）。作者受到博弈论的启发，仅保留正确的块匹配对。并采用博弈论框架剔除误匹配情况。在实际应用过程中，速度也很重要，作者也采用了一个匹配策略减少了对匹配策略的依赖。

In this work, we propose a novel, fast solution to the 3D ultrasound liver registration problem. Our contributions are fourfold: first, we integrate a fast outlier rejection approach to improve the result of a block-matching approach, second, we develop a method to use both the geometric consistency and the appearance information from block-matching to reject outliers, third, the (non-homogeneous quadratic) optimization function of the outlier rejection module is mapped to a homogeneous quadratic function to be solved efficiently using replicator dynamics, and fourth, we perform an extensive evaluation on real 3D imaging data. Finally, we demonstrate that the method is able to perform registrations at 8 Hz.
这篇文章，作者对3D超声肝脏配准问题提出了一个全新的、快速的解决方案。作者说他们的贡献集中在四个方面：

1.作者的算法集成了一个快速的离群排斥方法来提高块匹配的结果；

2.作者采用形貌约束和几何约束设计了离群排斥方法；

3.离群排斥策略中的非齐次二次函数被映射到齐次二次优化问题，并使用 Replicator Dynamics进行求解；

4.作者在真实的3D数据上进行了大量的实验。

Comment:其实吧，核心问题就一个...如何设计离群排斥算法。