POPULATION-BASED 4D CARDIAC ATLAS OF MOUSE

基于群体的小鼠 4D 心脏图谱

• 批准号: 7956898
• 负责人: RAIMOND Lester WINSLOW
• 金额: $ 0.55万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7956898
• 关键词: Address; Algorithms; Anatomic structures; Animals; Atlases; Brain; Cardiac; Characteristics; Computer Retrieval of Information on Scientific Projects Database; Computing Methodologies; Data; Disease; Funding; Grant; Heart; Image; In Vitro; Institution; Magnetic Resonance Imaging; Microscopic; Microscopy; Modeling; Mus; Population; Process; Property; Research; Research Personnel; Resolution; Resources; Science; Shapes; Source; Structure; System; Techniques; United States National Institutes of Health; Variant; in vivo; interest; population based

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.

该子项目是利用该技术的众多研究子项目之一 资源由 NIH/NCRR 资助的中心拨款提供。子项目及 研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金， 因此可以在其他 CRISP 条目中表示。列出的机构是 中心，不一定是研究者的机构。 该项目旨在开发基于规范群体的高时空分辨率小鼠心脏 4D 图集。一旦生成，该成像数据将用于量化种群内部和种群之间的形态和功能变化。此外，这些数据还可以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。这是通过利用配准算法来实现的，该算法在要对齐的结构之间建立一对一的对应关系。此类算法需要解决心脏的局部形状差异和动态特性的变化。我们成像科学中心的合作者开发了数学和计算方法，用于对大脑和体外动物心脏模型的解剖结构进行比较和统计推断[1]。我们希望扩展这些技术来捕获体内的动态特征 还有动物心脏模型。 对于初步实验，我们重点收集小鼠心脏的电影图像，这些图像以 80 微米或更小的近各向同性空间分辨率和 3-4 毫秒的时间分辨率获得。我们对显微 CT 和显微 MR 图像数据都感兴趣。通过您的贡献，我们希望能够收集此分辨率的图像。