首页> 外文会议>Image Processing pt.2; Progress in Biomedical Optics and Imaging; vol.7 no.30 >Temporal Registration of 2D X-ray Mammogram Using Triangular B-splines Finite Element Method (TBFEM)
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Temporal Registration of 2D X-ray Mammogram Using Triangular B-splines Finite Element Method (TBFEM)

机译:使用三角B样条有限元方法(TBFEM)进行二维X射线乳房X线照片的时间配准

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In this paper we develop a novel image processing technique to register two dimensional temporal mammograms for effective diagnosis and therapy. Our registration framework is founded upon triangular B-spline finite element method (TBFEM). In contrast to tensor-product B-splines, which is widely used in medical imaging, triangular B-splines are much more powerful, associated with many desirable advantages for image registration, such as flexible triangular domain, local control, space-varying smoothness, and sharp feature modeling. Empowered by the rigorous theory of triangular B-splines, our method can explicitly model the transformation between temporal mammogram pairs over irregular region of interest (ROI), using a collection of triangular B-splines. In addition, it is also capable of describing C~0 continuous deformation at the interfaces between different elastic tissues, while the overall displacement field is smooth. Our registration process consists of two steps: 1) The template image is first nonlinearly deformed using TBFEM model, subject to pre-segmented feature constraints; 2) The deformed template image is further perturbed by applying pseudo image forces, aiming to reducing intensity-based discrepancies. The proposed registration framework has been tested extensively on practical clinical data, and the experimental results demonstrates that the registration accuracy is improved comparing to using conventional FEMs. Besides, the modeling of local C~0 continuities of the displacement field helps to further increase the registration quality considerably.
机译:在本文中,我们开发了一种新颖的图像处理技术来记录二维时间乳腺X线照片,以进行有效的诊断和治疗。我们的注册框架基于三角B样条有限元方法(TBFEM)。与广泛用于医学成像的张量积B样条相比,三角形B样条的功能要强大得多,并具有许多理想的图像配准优势,例如灵活的三角形域,局部控制,时空平滑,和清晰的特征建模。在三角B样条的严格理论的支持下,我们的方法可以使用三角B样条的集合显式地对不规则感兴趣区域(ROI)上的时间X线照片对之间的转换进行建模。另外,它还能够描述不同弹性组织之间的界面处的C〜0连续变形,而整体位移场是平滑的。我们的配准过程包括两个步骤:1)首先使用TBFEM模型对模板图像进行非线性变形,但要遵守预先分割的特征约束; 2)变形后的模板图像通过施加伪图像力而进一步受到干扰,旨在减少基于强度的差异。所提出的注册框架已经在实际临床数据上进行了广泛的测试,实验结果表明,与使用常规FEM相比,注册准确性得到了提高。此外,对位移场的局部C〜0连续性进行建模有助于进一步提高配准质量。

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