Golby Lab, Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA.
Neuroimage. 2012 Mar;60(1):456-70. doi: 10.1016/j.neuroimage.2011.11.014. Epub 2011 Dec 2.
The overall goal of this research is the design of statistical atlas models that can be created from normal subjects, but may generalize to be applicable to abnormal brains. We present a new style of joint modeling of fMRI, DTI, and structural MRI. Motivated by the fact that a white matter tract and related cortical areas are likely to displace together in the presence of a mass lesion (brain tumor), in this work we propose a rotation and translation invariant model that represents the spatial relationship between fiber tracts and anatomic and functional landmarks. This landmark distance model provides a new basis for representation of fiber tracts and can be used for detection and prediction of fiber tracts based on landmarks. Our results indicate that the measured model is consistent across normal subjects, and thus suitable for atlas building. Our experiments demonstrate that the model is robust to displacement and missing data, and can be successfully applied to a small group of patients with mass lesions.
本研究的总体目标是设计能够从正常受试者创建的统计图谱模型，但可以推广到异常大脑。我们提出了一种新的 fMRI、DTI 和结构 MRI 联合建模风格。鉴于在存在肿块病变（脑瘤）的情况下，白质束和相关皮质区域可能一起移位的事实，在这项工作中，我们提出了一种旋转和平移不变模型，该模型表示纤维束与解剖和功能标记之间的空间关系。这种地标距离模型为纤维束的表示提供了新的基础，并可用于基于地标检测和预测纤维束。我们的结果表明，在正常受试者中测量的模型是一致的，因此适合构建图谱。我们的实验表明，该模型对位移和缺失数据具有鲁棒性，并且可以成功应用于一小群患有肿块病变的患者。
