POPULATION-BASED 4D CARDIAC ATLAS OF MOUSE

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 该项目的目的是开发一个基于标准种群的高时空分辨率的4D小鼠心脏图谱。一旦产生，这些成像数据将被用来量化种群内和种群之间的形态和功能差异。此外，这些数据可能用于心脏图像的自动分割或检查疾病过程。 通过将图像数据放置到标准坐标系中来研究解剖和功能的可变性。这通过利用配准算法来实现，该配准算法在要对齐的结构之间建立一对一的对应关系。这样的算法需要处理心脏的局部形状差异和动态特性的变化。我们成像科学中心的合作者已经开发出数学和计算方法，用于比较和统计大脑和体外动物心脏模型的解剖结构[1]。我们希望将这些技术扩展到捕捉体内的动态特征 动物心脏模型也是如此。 作为初步实验，我们将重点收集在空间分辨率为80um或更低、时间分辨率为3-4ms的接近各向同性的小鼠心脏的电影图像。我们会对显微CT和显微MR图像数据感兴趣。有了您的贡献，我们希望能够以这种分辨率收集图像。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project is aimed at developing a normative population based 4D atlas of the mouse heart at high spatio-temporal resolution. Once generated, this imaging data would be used to quantify the morphological and functional variation within and between the populations. Additionally these data could potentially be used in automatic segmentation of cardiac images or to examine the disease process. Anatomical and functional variability is studied by placement of image data into a standard coordinate system. This achieved by utilizing registration algorithms that establish a one to one correspondence between the structures to be aligned. Such algorithms require addressing both the local shape differences and the variation in dynamic properties of the heart. Our collaborators in center for imaging science have developed mathematical and computational methods for comparison and statistical inference regarding anatomic structures in brain and in vitro animal heart model [1]. We would like to extend these techniques to capture dynamic characteristics of in vivo animal heart models as well. For preliminary experimentation we are focusing on collecting cine images of mouse heart acquired at near isotropic spatial resolution of 80 um or less with temporal resolution of 3-4 ms. We would be interested in both microCT and microscopic MR image data. With your contributon, we hope to be able to collect images at this resolution.