Image Segmentation, Quantitative Analysis And Three-dimensional Visualization In Spine MRI

Health is one of the main topics in our modern society. As the production of technology and human wisdom, medical imaging, which provides a non-intervention overview of inner structures of our bodies and great help in diagnosis and cure, has pushed medical society significantly. Combining fields like information science and medicine, medical image process and analysis is making another push in the progress of medicine digitally, automatically and intelligently.In this paper, research is done on segmenting, quantitative analyzing and visualizing spine MRI. The main points are as follow:(1) It is proposed that the vertebral structure is segmented with improved active appearance model (AAM). Considering the assumption of Gaussian distribution of training data in classic AAM, the model built with principle component analysis (PCA) is insufficient in describing the details of shape and texture. So PCA is replaced by independent component analysis (ICA) in building shape model and texture model in AAM model building. And the spinal vertebral bodies are segmented with this improved AAM.(2) Based on segmenting spinal vertebral structure, a series of quantitative extraction and analysis are presented, aiming at obtaining quantitative physiological and pathological features in spine MRI. Firstly, lumbar curve is optimally fitted based on minimum description length (MDL); curvature operator is then introduced into computing lumbar lordosis angles. Secondly, the distribution of intensity in local lumbar disc region is detected through intensity projection; based on this information, lumbar discs are segmented with a fast and unsupervised Markov random field (MRF). Thirdly, the quantitative lumbar disc herniation is evaluated with the cooperation of lumbar curve and segmented discs.(3) On the visualization platform provided with Visualization ToolKit (VTK), spine CT and MRI are three-dimensionally visualized respectively with marching cubes and ray casting algorithm.The experiments of each point are made. The segmentation error with improved AAM is lower than that of classic AAM. The optimal lumbar curve and lordosis angles are subjective and accurate. In segmenting lumbar disc, the temporal cost is much lower while segmentation accuracy is kept. The quantitative lumbar disc herniation is of great clinical value.