基于表面的脑三维图像变形技术。

A surface-based technique for warping three-dimensional images of the brain.

机构信息

Sch. of Med., California Univ., Los Angeles, CA.

出版信息

IEEE Trans Med Imaging. 1996;15(4):402-17. doi: 10.1109/42.511745.

Abstract

The authors have devised, implemented, and tested a fast, spatially accurate technique for calculating the high-dimensional deformation field relating the brain anatomies of an arbitrary pair of subjects. The resulting three-dimensional (3-D) deformation map can be used to quantify anatomic differences between subjects or within the same subject over time and to transfer functional information between subjects or integrate that information on a single anatomic template. The new procedure is based on developmental processes responsible for variations in normal human anatomy and is applicable to 3-D brain images in general, regardless of modality. Hybrid surface models known as Chen surfaces (based on superquadrics and spherical harmonics) are used to efficiently initialize 3-D active surfaces, and these then extract from both scans the developmentally fundamental surfaces of the ventricles and cortex. The construction of extremely complex surface deformation maps on the internal cortex is made easier by building a generic surface structure to model it. Connected systems of parametric meshes model several deep sulci whose trajectories represent critical functional boundaries. These sulci are sufficiently extended inside the brain to reflect subtle and distributed variations in neuroanatomy between subjects. The algorithm then calculates the high-dimensional volumetric warp (typically with 3842x256x3 approximately 0.1 billion degrees of freedom) deforming one 3-D scan into structural correspondence with the other. Integral distortion functions are used to extend the deformation field required to elastically transform nested surfaces to their counterparts in the target scan. The algorithm's accuracy is tested, by warping 3-D magnetic resonance imaging (MRI) volumes from normal subjects and Alzheimer's patients, and by warping full-color 1024(3 ) digital cryosection volumes of the human head onto MRI volumes. Applications are discussed, including the transfer of multisubject 3-D functional, vascular, and histologic maps onto a single anatomic template; the mapping of 3-D brain atlases onto the scans of new subjects; and the rapid detection, quantification, and mapping of local shape changes in 3-D medical images in disease and during normal or abnormal growth and development.

摘要

作者设计、实现并测试了一种快速、精确的技术,用于计算任意一对受试者之间的大脑解剖结构的高维变形场。所得的三维(3-D)变形图可用于量化受试者之间或同一受试者随时间的解剖差异,并在受试者之间转移功能信息或在单个解剖模板上整合该信息。新方法基于导致正常人体解剖结构变化的发育过程,适用于一般的 3-D 脑图像,而与模态无关。称为 Chen 曲面(基于超二次曲面和球谐函数)的混合曲面模型用于有效地初始化 3-D 主动曲面,然后从两个扫描中提取脑室和皮层的发育基础曲面。通过构建通用曲面结构对其进行建模,使构建非常复杂的内部皮层曲面变形图变得更加容易。参数化网格的连接系统模型化了几个深沟,其轨迹代表关键的功能边界。这些沟在大脑内部延伸得足够远,以反映受试者之间神经解剖学的细微和分布差异。然后,算法计算将一个 3-D 扫描变形为与另一个扫描结构对应的高维体积变形(通常具有大约 3842x256x3 即 0.1 亿个自由度)。积分变形函数用于扩展变形场,以便将嵌套曲面弹性变换为目标扫描中的对应曲面。通过对正常受试者和阿尔茨海默病患者的 3-D 磁共振成像(MRI)体积进行变形以及将人类头部的全彩色 1024(3)数字冷冻切片体积变形到 MRI 体积上,测试了算法的准确性。讨论了应用,包括将多受试者 3-D 功能、血管和组织学图转移到单个解剖模板上;将 3-D 脑图谱映射到新受试者的扫描上;以及在疾病期间以及在正常或异常生长和发育过程中快速检测、量化和映射 3-D 医学图像中的局部形状变化。

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