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.

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