Sherbondy Anthony, Akers David, Mackenzie Rachel, Dougherty Robert, Wandell Brian
Department of Electrical Engineering, James H. Clark Center, 318 Campus Dr., Room S324, Stanford University, Stanford, CA 94305, USA.
IEEE Trans Vis Comput Graph. 2005 Jul-Aug;11(4):419-30. doi: 10.1109/TVCG.2005.59.
Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging method that can be used to measure local information about the structure of white matter within the human brain. Combining DTI data with the computational methods of MR tractography, neuroscientists can estimate the locations and sizes of nerve bundles (white matter pathways) that course through the human brain. Neuroscientists have used visualization techniques to better understand tractography data, but they often struggle with the abundance and complexity of the pathways. In this paper, we describe a novel set of interaction techniques that make it easier to explore and interpret such pathways. Specifically, our application allows neuroscientists to place and interactively manipulate box or ellipsoid-shaped regions to selectively display pathways that pass through specific anatomical areas. These regions can be used in coordination with a simple and flexible query language which allows for arbitrary combinations of these queries using Boolean logic operators. A representation of the cortical surface is provided for specifying queries of pathways that may be relevant to gray matter structures and for displaying activation information obtained from functional magnetic resonance imaging. By precomputing the pathways and their statistical properties, we obtain the speed necessary for interactive question-and-answer sessions with brain researchers. We survey some questions that researchers have been asking about tractography data and show how our system can be used to answer these questions efficiently.
扩散张量成像（DTI）是一种磁共振成像方法，可用于测量有关人类大脑白质结构的局部信息。将DTI数据与磁共振纤维束成像的计算方法相结合，神经科学家可以估计穿过人类大脑的神经束（白质通路）的位置和大小。神经科学家已使用可视化技术来更好地理解纤维束成像数据，但他们常常在通路的丰富性和复杂性方面遇到困难。在本文中，我们描述了一套新颖的交互技术，这些技术使探索和解释此类通路变得更加容易。具体而言，我们的应用程序允许神经科学家放置并交互式地操纵盒子或椭圆形区域，以选择性地显示穿过特定解剖区域的通路。这些区域可以与一种简单灵活的查询语言配合使用，该语言允许使用布尔逻辑运算符对这些查询进行任意组合。提供了皮质表面的表示，用于指定可能与灰质结构相关的通路查询，并用于显示从功能磁共振成像获得的激活信息。通过预先计算通路及其统计特性，我们获得了与脑研究人员进行交互式问答环节所需的速度。我们调查了研究人员一直在询问的有关纤维束成像数据的一些问题，并展示了我们的系统如何能够有效地回答这些问题。
