POPULATION-BASED 4D CARDIAC ATLAS OF MOUSE

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 该项目旨在开发一个规范的人口为基础的高时空分辨率的小鼠心脏的4D图谱。一旦生成，该成像数据将用于量化群体内和群体之间的形态和功能变化。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变异性。这通过利用在待对准的结构之间建立一一对应的配准算法来实现。这种算法需要解决心脏的局部形状差异和动态特性的变化。我们在成像科学中心的合作者已经开发了数学和计算方法，用于比较和统计推断大脑和体外动物心脏模型中的解剖结构[1]。我们希望扩展这些技术，以捕捉体内的动态特性， 动物心脏模型也是如此。 对于初步实验，我们专注于收集电影图像的小鼠心脏采集在近各向同性的空间分辨率为80微米或更低的时间分辨率为3-4毫秒。我们将在microCT和显微镜MR图像数据感兴趣。有了你的贡献，我们希望能够收集到这个分辨率的图像。

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.