Nowinski Wieslaw L, Prakash Bhanu, Volkau Ihar, Ananthasubramaniam Anand, Beauchamp Norman J
Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, #07-01 Matrix, Singapore.
Acad Radiol. 2006 May;13(5):652-63. doi: 10.1016/j.acra.2006.01.051.
A near real-time and fully automatic method for calculation of the midsagittal plane (MSP) for magnetic resonance (MR) diffusion and perfusion images is introduced.
The method is based on the Kullback-Leibler's (KL) measure quantifying the difference between two intensity distributions. The MSP is a sagittal plane with the highest KL measure. The method was validated quantitatively for 61 diffusion-weighted imaging (DWI), cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), peak height (PKHT), and time to peak (TPP) data sets of 11 stroke patients based on the ground truth provided by two raters.
Average angular errors are less than 1 degrees for DWI and less than 2 degrees for CBF and CBV. Average distance errors measured in the worst case (on the brain's bounding box) are less than 2.5 mm for DWI and less than 5 mm for CBF and CBV. This algorithmic accuracy is at the level of interrater variability. Results obtained for the other perfusions maps (MTT, PKHT, TTP) were inferior; therefore, processing of CBF or CBV is preferred for accurate and robust calculation of the MSP from perfusion maps. Calculation of the MSP takes about half a second on a standard computer.
The proposed method is near real-time and fully automatic, and neither user interaction nor parameter setting is needed. It does not require preprocessing of data. The method potentially is useful in rapid and automated processing of MR stroke diffusion and perfusion images.
介绍一种用于磁共振(MR)扩散和灌注图像中矢状面(MSP)计算的近实时全自动方法。
该方法基于库尔贝克-莱布勒(KL)测度,用于量化两个强度分布之间的差异。MSP是具有最高KL测度的矢状面。基于两位评估者提供的真实数据,对11例中风患者的61个扩散加权成像(DWI)、脑血流量(CBF)、脑血容量(CBV)、平均通过时间(MTT)、峰值高度(PKHT)和达峰时间(TPP)数据集进行了定量验证。
DWI的平均角度误差小于1度,CBF和CBV的平均角度误差小于2度。在最坏情况下(在脑边界框上)测量的平均距离误差,DWI小于2.5毫米,CBF和CBV小于5毫米。这种算法精度处于评估者间变异性水平。其他灌注图(MTT、PKHT、TTP)获得的结果较差;因此,为了从灌注图中准确且稳健地计算MSP,首选处理CBF或CBV。在标准计算机上计算MSP大约需要半秒。
所提出的方法是近实时且全自动的,既不需要用户交互也不需要参数设置。它不需要数据预处理。该方法可能有助于快速自动处理MR中风扩散和灌注图像。