Infant Brain Measurement and Super-Resolution Atlas Construction

婴儿大脑测量和超分辨率图谱构建

• 批准号: 8583365
• 负责人: Dinggang Shen
• 金额: $ 58.38万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-26 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8583365
• 关键词: 1 year old; 2 year old; Address; Adult; Age-Years; Algorithms; Atlases; Birth; Birth Intervals; Brain; Brain imaging; Brain region; Brain scan; Communities; Computer software; Computing Methodologies; Data; Data Analyses; Data Set; Development; Diffusion Magnetic Resonance Imaging; Diffusion weighted imaging; Due Process; Environment; Future; Gray unit of radiation dose; Growth; Housing; Human; Image; Infant; Informatics; Knowledge; Lead; Life; Magnetic Resonance Imaging; Maps; Measurement; Measures; Medical Staff; Methods; Neonatal; Neurodevelopmental Disorder; Noise; Pattern; Performance; Phase; Population; Process; Psychotic Disorders; Public Health; Research; Resolution; Resources; Scanning; Shapes; Shoulder; Signal Transduction; Structure; Surface; Techniques; Time; Tissues; Variant; Weight; base; brain size; computerized tools; critical period; fetal; follow-up; image registration; imaging Segmentation; imaging modality; improved; insight; multimodality; myelination; neonate; neuroimaging; novel; population based; public health relevance; reconstruction; stem; tool; white matter change

DESCRIPTION (provided by applicant): The human brain undergoes a dynamic phase of development with rapid structural and functional growth in the first year of life. Insight into thi critical period of development is of paramount importance for understanding the neurodevelopmental origins of psychiatric illness, since brain alterations that are associated with psychosis and other major psychiatric illnesses often occur early during fetal or neonatal life. The recent availability of infant neuroimaging data is making increasingly feasible the precise characterization of development patterns in this period of time. However, computational tools that are dedicated to this purpose are still rare due to the following challenges: (1) Infant scans suffer from significantly lower spatial resolution due to the smaller brain size; (2) Limited by scn time, the achievable signal-to-noise ratio for diffusion-weighted images is typically low; (3) The rapid myelination process results in significant variation of image contrast across different brain regions, which can easily confuse existing computational methods; (4) Techniques developed for adult brain analysis are not directly transferable to infants. This project shoulders the challenging task of overcoming important technological hurdles in creating high- precision computational tools that will automate the quantification of brain development in the first year of life. In Aim 1, we will create a 4D multimodality-guided, level-set-based framework for simultaneous segmentation and registration of serial brain scans acquired from birth to one year of age. This will allow low-contrast images (e.g., the isointense 3- and 6-month scans) to be segmented more effectively by borrowing multimodality information from early time-point (2-week) and/or later time-point (1-year) scans. In Aim 2, we will create a 4D cortical surface reconstruction method for consistent surface reconstruction across different time points. This will help alleviate the imprecision stemming from structural ambiguities in the surface reconstruction process due to low image contrast. In Aim 3, we will create a clustering-based hierarchically organized registration framework that will harness the manifold of anatomical variation of the image population for effective registration of infant brains. This will aid effectve registration of images with large structural differences to a common space for population-based early brain development studies. In Aim 4, we will create super-resolution atlases for infant brains at each time point by using a novel patch-based sparse representation technique. These atlases, when used as templates for brain registration, will lead to significant performance improvement due to their significantly improved structural clarity. All created tools and super-resolution atlases will be integrated into a dedicated infant-brain-analysis software package and made freely available to the research community.

描述（申请人提供）：人的大脑在生命的第一年经历了一个动态的发展阶段，结构和功能的快速增长。深入了解这一发育的关键时期对于理解精神疾病的神经发育起源至关重要，因为大脑的改变与精神疾病有关