Changizi Neda, Hamarneh Ghassan, Ishaq Omer, Ward Aaron, Tam Roger
Medical Image Analysis Lab, Simon Fraser University, Canada.
Med Image Comput Comput Assist Interv. 2010;13(Pt 3):17-24. doi: 10.1007/978-3-642-15711-0_3.
Changes in corpus callosum (CC) size are typically quantified in clinical studies by measuring the CC cross-sectional area on a midsagittal plane. We propose an alternative measurement plane based on the role of the CC as a bottleneck structure in determining the rate of interhemispheric neural transmission. We designate this plane as the Minimum Corpus Callosum Area Plane (MCCAP), which captures the cross section of the CC that best represents an upper bound on interhemispheric transmission. Our MCCAP extraction method uses a nested optimization framework, segmenting the CC as it appears on each candidate plane, using registration-based segmentation. We demonstrate the robust convergence and high accuracy of our method for magnetic resonance images and present preliminary clinical results showing higher sensitivity to disease-induced atrophy.
在临床研究中，胼胝体（CC）大小的变化通常通过测量矢状中面上的CC横截面积来量化。基于CC作为决定半球间神经传递速率的瓶颈结构的作用，我们提出了一种替代测量平面。我们将此平面指定为最小胼胝体面积平面（MCCAP），它捕捉到的CC横截面最能代表半球间传递的上限。我们的MCCAP提取方法使用嵌套优化框架，通过基于配准的分割，对每个候选平面上出现的CC进行分割。我们展示了该方法在磁共振图像上的稳健收敛性和高精度，并给出了初步临床结果，显示对疾病引起的萎缩具有更高的敏感性。
