Multiscale joint segmentation and registration of image morphology
Multiscale joint segmentation and registration of image morphology
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DOI：
10.1109/tpami.2007.1120
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发表时间：
2007-12-01
影响因子：
23.6
通讯作者：
Rumpf, Martin
中科院分区：
文献类型：
--
作者：
Droske, Marc;Rumpf, Martin
多模态图像配准显着受益于之前的去噪和结构分割，反之亦然。特别是，不同图像模态的组合信息使得分割更加稳健。事实上，图像处理中的基本任务是高度相互依赖的。提出了一种变分方法，它将相应边缘的检测、边缘保留去噪以及通过一对具有结构对应的图像的非刚性变形进行形态学配准。图像函数的形态被分为由边缘集组成的奇异部分和由水平集集合上的法线场表示的规则部分。应用Mumford-Shah型自由不连续问题来处理变形下的奇异形态和相应边缘的匹配。规则形态的匹配通过第二个贡献来量化，该贡献比较变形法线和变形位置处的法线。最后，非线性弹性能量控制变形本身并确保平滑性和注入性。基于相场近似的多尺度方法产生了有效且高效的算法。数值实验强调了所提出方法的稳健性，并展示了在医学图像上的应用。
Multimodal image registration significantly benefits from previous denoising and structure segmentation and vice versa. In particular, combined information of different image modalities makes segmentation significantly more robust. Indeed, fundamental tasks in image processing are highly interdependent. A variational approach is presented, which combines the detection of corresponding edges, an edge preserving denoising, and the morphological registration via a nonrigid deformation for a pair of images with structural correspondence. The morphology of an image function is split into a singular part consisting of the edge set and a regular part represented by the field of normals on the ensemble of level sets. A Mumford- Shah type free discontinuity problem is applied to treat the singular morphology and the matching of corresponding edges under the deformation. The matching of the regular morphology is quantified by a second contribution, which compares deformed normals and normals at deformed positions. Finally, a nonlinear elastic energy controls the deformation itself and ensures smoothness and injectivity. A multiscale approach that is based on a phase field approximation leads to an effective and efficient algorithm. Numerical experiments underline the robustness of the presented approach and show applications on medical images.