医学
图像质量
神经影像学
壳核
神经解剖学
核医学
白质
人工智能
规范化(社会学)
信号平均
图像分辨率
计算机视觉
体素
磁共振成像
模式识别(心理学)
图像配准
计算机科学
图像(数学)
放射科
解剖
模拟信号
信号传递函数
数字信号处理
精神科
社会学
人类学
内分泌学
计算机硬件
作者
Colin J. Holmes,Rick Hoge,D. Louis Collins,Roger P. Woods,Arthur W. Toga,Alan C. Evans
出处
期刊:Journal of Computer Assisted Tomography
[Ovid Technologies (Wolters Kluwer)]
日期:1998-03-01
卷期号:22 (2): 324-333
被引量:1262
标识
DOI:10.1097/00004728-199803000-00032
摘要
With the advent of noninvasive neuroimaging, a plethora of digital human neuroanatomical atlases has been developed. The accuracy of these atlases is constrained by the resolution and signal-gathering powers of available imaging equipment. In an attempt to circumvent these limitations and to produce a high resolution in vivo human neuroanatomy, we investigated the usefulness of intrasubject registration for post hoc MR signal averaging.Twenty-seven high resolution (7 x 0.78 and 20 x 1.0 mm3) T1-weighted volumes were acquired from a single subject, along with 12 double echo T2/proton density-weighted volumes. These volumes were automatically registered to a common stereotaxic space in which they were subsampled and intensity averaged. The resulting images were examined for anatomical quality and usefulness for other analytical techniques.The quality of the resulting image from the combination of as few as five T1 volumes was visibly enhanced. The signal-to-noise ratio was expected to increase as the root of the number of contributing scans to 5.2, n = 27. The improvement in the n = 27 average was great enough that fine anatomical details, such as thalamic subnuclei and the gray bridges between the caudate and putamen, became crisply defined. The gray/white matter boundaries were also enhanced, as was the visibility of any finer structure that was surrounded by tissue of varying T1 intensity. The T2 and proton density average images were also of higher quality than single scans, but the improvement was not as dramatic as that of the T1 volumes.Overall, the enhanced signal in the averaged images resulted in higher quality anatomical images, and the data lent themselves to several postprocessing techniques. The high quality of the enhanced images permits novel uses of the data and extends the possibilities for in vivo human neuroanatomy.
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