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中文摘要
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描述(由申请人提供):该项目的总体目标是显着提高胎儿MRI诊断,分析和预后高危妊娠的能力。通过胎儿MRI获得的准确分析对于评估影响约0.5%妊娠的胎儿中枢神经系统发育障碍的高度可变病因学和知之甚少的病理生理学至关重要。然而,胎儿MRI受限于二维采集,这是由于可从小胎儿大脑获得的小信号,以及间歇性胎儿运动破坏了高级三维体积MRI所需的空间编码。为了解决这一限制并揭示胎儿MRI的能力,我们提出了新的成像和图像处理技术,在该项目中追求四个特定目标;目标1是我们总体目标的关键,涉及胎儿大脑三维高空间分辨率体积T2 w图像的超分辨率重建。目的二是建立胎儿脑的时空图谱。目的3:比较二维MRI、二维超声和三维MRI对胎儿脑生物学的测量和评价。最后,在目标4中,考虑使用3D胎儿MRI改进脑室扩大的评估。心室肥大是最常见的胎儿脑部异常,影响约0.1- 0.2%的胎儿。目的1和2涉及临床使用的新技术的开发,目的3和4涉及技术开发和假设检验,以了解与当前实践相比,使用开发的技术在胎儿脑异常的评价、诊断和分析方面取得了多大的改进。
英文摘要
DESCRIPTION (provided by applicant): The overall objective of this project is to dramatically improve the capability of fetal MRI for diagnosis, analysis, and prognosis of high-risk pregnancies. Accurate analysis obtained by fetal MRI is crucial in evaluating the highly variable aetiology and poorly understood pathophysiology of fetal central nervous system developmental disorders which affect about one-half percent of pregnancies. Nevertheless, fetal MRI is limited to two- dimensional acquisitions by the small signal available from the small fetal brain, and by intermittent fetal motion that disrupts spatial encoding necessary for advanced three-dimensional volumetric MRI. In order to address this limitation and reveal the power of fetal MRI, we propose novel imaging and image processing technology pursuing four specific aims in this project; Aim 1, which is pivotal to our overall objective, involves super- resolution reconstruction of three-dimensional high spatial resolution volumetric T2w images of the fetal brain. Aim 2 involves the construction of a spatiotemporal fetal brain atlas. Aim 3 involves the comparison of fetal brain biometry and evaluation using 2D MRI, 2D sonography and 3D MRI. Finally in Aim 4 improved assessment of ventriculomegaly is considered using 3D fetal MRI. Ventriculomegaly is the most frequently observed fetal brain abnormality affecting about 0.1-0.2 percent of fetuses. Aims 1 and 2 involve the development of new technology for clinical use and Aims 3 and 4 involve both technical developments and hypothesis tests to see how much improvement is achieved in the evaluation, diagnosis, and analysis of fetal brain abnormalities using the developed technology as compared to the current practice.
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Motion Compensated fMRI for Pre-Surgical Planning in Epilepsy
  • 批准号:
    10659634
  • 项目类别:
  • 资助金额:
    $67.11万
  • 财政年份:
    2023
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
Machine learning algorithms to analyze large medical image datasets
  • 批准号:
    10434022
  • 项目类别:
  • 资助金额:
    $37.61万
  • 财政年份:
    2021
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
Machine learning algorithms to analyze large medical image datasets
  • 批准号:
    10182522
  • 项目类别:
  • 资助金额:
    $36.96万
  • 财政年份:
    2021
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
Machine learning algorithms to analyze large medical image datasets
  • 批准号:
    10584569
  • 项目类别:
  • 资助金额:
    $37.61万
  • 财政年份:
    2021
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
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