Shilling Richard Z, Robbie Trevor Q, Bailloeul Timothée, Mewes Klaus, Mersereau Russell M, Brummer Marijn E
Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA.
IEEE Trans Med Imaging. 2009 May;28(5):633-44. doi: 10.1109/TMI.2008.2007348. Epub 2008 Oct 31.
A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach.
提出了一种用于磁共振成像（MRI）的新型超分辨率重建（SRR）框架。其目的是生成图像引导下微创脑手术所需的高分辨率和高对比度图像。输入数据是围绕共同频率编码轴以规则角间距旋转的多个二维多层反转恢复MRI扫描。输出是一个各向同性高分辨率的三维体积。反转过程类似于局部投影重建问题。基于凸集投影（POCS）形式主义的迭代重建算法。结果表明，在临床扫描仪上进行的模拟体模研究、离体和活体人脑扫描中分辨率得到了提高。与先前发表的SRR方法的比较表明，该方法具有良好的特性。
