Banerjee Sreerup, Dixit Sudeepa, Fox Mark, Pal Anupam
Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India; and
Department of Biological Sciences and Bioengineering, Indian Institute of Technology Kanpur, Kanpur, India; and.
Am J Physiol Gastrointest Liver Physiol. 2015 Apr 15;308(8):G652-63. doi: 10.1152/ajpgi.00095.2014. Epub 2014 Dec 24.
Magnetic resonance imaging (MRI) has advantages for the assessment of gastrointestinal structures and functions; however, processing MRI data is time consuming and this has limited uptake to a few specialist centers. This study introduces a semiautomatic image processing system for rapid analysis of gastrointestinal MRI. For assessment of simpler regions of interest (ROI) such as the stomach, the system generates virtual images along arbitrary planes that intersect the ROI edges in the original images. This generates seed points that are joined automatically to form contours on each adjacent two-dimensional image and reconstructed in three dimensions (3D). An alternative thresholding approach is available for rapid assessment of complex structures like the small intestine. For assessment of dynamic gastrointestinal function, such as gastric accommodation and emptying, the initial 3D reconstruction is used as reference to process adjacent image stacks automatically. This generates four-dimensional (4D) reconstructions of dynamic volume change over time. Compared with manual processing, this semiautomatic system reduced the user input required to analyze a MRI gastric emptying study (estimated 100 vs. 10,000 mouse clicks). This analysis was not subject to variation in volume measurements seen between three human observers. In conclusion, the image processing platform presented processed large volumes of MRI data, such as that produced by gastric accommodation and emptying studies, with minimal user input. 3D and 4D reconstructions of the stomach and, potentially, other gastrointestinal organs are produced faster and more accurately than manual methods. This system will facilitate the application of MRI in gastrointestinal research and clinical practice.
磁共振成像(MRI)在评估胃肠道结构和功能方面具有优势;然而,处理MRI数据耗时,这使得其应用仅限于少数专业中心。本研究引入了一种用于快速分析胃肠道MRI的半自动图像处理系统。对于评估如胃等较简单的感兴趣区域(ROI),该系统沿与原始图像中ROI边缘相交的任意平面生成虚拟图像。这会生成种子点,这些种子点会自动连接以在每个相邻的二维图像上形成轮廓并进行三维(3D)重建。还有一种替代的阈值处理方法可用于快速评估如小肠等复杂结构。对于评估动态胃肠道功能,如胃容纳和排空,初始的3D重建用作参考以自动处理相邻的图像堆栈。这会生成随时间变化的动态体积变化的四维(4D)重建。与手动处理相比,这种半自动系统减少了分析MRI胃排空研究所需的用户输入(估计为100次与10,000次鼠标点击)。该分析不受三位人类观察者之间体积测量差异的影响。总之,所展示图像处理平台以最少的用户输入处理了大量的MRI数据,如胃容纳和排空研究产生的数据。胃以及可能的其他胃肠道器官的3D和4D重建比手动方法更快、更准确地生成。该系统将促进MRI在胃肠道研究和临床实践中的应用。