通知公告

学术报告:Advances in diffusion MRI acquisition and reconstructio

2017-04-27 09:50:55

电子科技大学核磁共振中心
中古联合实验室特邀英国牛津大学吴文川博士,与我院师生分享他在扩散磁共振成像技术领域的研究及进展。具体安排如下,欢迎感兴趣的教师和博士生参加。 一、 时间:2017年5月2日星期二上午10:00-11:30 二、 地点:信息医学研究中心131会议室 三、 主题:Advances in diffusion MRI acquisition and reconstruction 四、 主持人:Pedro Antonio Valdes Sosa 五、 承办单位:生命科学与技术学院 六、 交流内容: Advances in diffusion MRI acquisition and reconstruction Diffusion MRI is a standard imaging tool in clinical neurology, and is becoming increasingly important for neuroscience studies due to its ability to depict complex neuro-anatomy (e.g., white matter connectivity). High spatial resolution is desired in diffusion MRI as it can provide the ability to resolve small brain structures, enabling investigations of detailed white matter architecture. A major challenge for in vivo high-resolution diffusion MRI is the low signal-to-noise ratio (SNR). In the first part of my talk, I will describe a new approach we proposed to improve the SNR of diffusion MRI data, which combines two highly compatible methods, ultra-high field and three-dimensional multi-slab acquisition. In vivo results demonstrate that using the new method, high-quality diffusion MRI data with ~1mm isotropic resolution can be achieved. Another challenge faced by diffusion MRI is the long scan time, as typically a large number of diffusion volumes (directions) are acquired. In the second part of my talk, I’ll introduce a new method we proposed to improve the reconstruction of diffusion MRI data. As diffusion volumes contain an abundance of common features (e.g. structural boundaries, mean signal attenuation), yet each volume is usually reconstructed independently. We proposed to integrate Gaussian processes into image reconstruction to leverage shared information between the k and q domains to reduce image artifacts associated with parallel imaging. I’ll show some preliminary results with 12 folds acceleration (MB=4, R=3, 7T), in which the proposed method clearly outperforms conventional reconstruction methods. 主讲人简介:英国牛津大学磁共振物理博士。主要从事扩散磁共振成像在神经科学研究;主要包括高分辨率,高信噪比扩散磁共振成像技术;超高场(7T)磁共振成像技术;磁共振采集和重建方法;等。目前其团队提出使用高斯过程对扩散磁共振信号进行建模,并基于模型进行图像重建,利用图像数据中的冗余信息提高重建算法的性能。在Magnetic Resonance Imaging等国际期刊发表论文10篇;专利2项。