Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
IEEE Trans Med Imaging. 2013 Sep;32(9):1647-56. doi: 10.1109/TMI.2013.2262055. Epub 2013 May 7.
Real-time ultrasound image acquisition is a pivotal resource in the medical community, in spite of its limited image quality. This poses challenges to image registration methods, particularly to those driven by intensity values. We address these difficulties in a novel diffeomorphic registration technique for tumor tracking in series of 2-D liver ultrasound. Our method has two main characteristics: 1) each voxel is described by three image features: intensity, local phase, and phase congruency; 2) we compute a set of forces from either local information (Demons-type of forces), or spatial correspondences supplied by a block-matching scheme, from each image feature. A family of update deformation fields which are defined by these forces, and inform upon the local or regional contribution of each image feature are then composed to form the final transformation. The method is diffeomorphic, which ensures the invertibility of deformations. The qualitative and quantitative results yielded by both synthetic and real clinical data show the suitability of our method for the application at hand.
实时超声图像采集是医学领域的关键资源，尽管其图像质量有限。这对图像配准方法提出了挑战，特别是对那些基于强度值的方法。我们在一种新的用于二维肝脏超声序列中肿瘤跟踪的变形配准技术中解决了这些困难。我们的方法有两个主要特点：1）每个体素由三个图像特征描述：强度、局部相位和相位一致性；2）我们从每个图像特征计算一组力，这些力要么来自局部信息（Demons 类型的力），要么来自块匹配方案提供的空间对应关系。然后，由这些力定义的一组更新变形场，并根据每个图像特征的局部或区域贡献进行组合，形成最终的变换。该方法是可变形的，这确保了变形的可逆性。合成和真实临床数据的定性和定量结果表明，我们的方法适用于当前的应用。
