Yoo K S, Wang G, Rubinstein J T, Vannier M W
From the Department of Medical Engineering, Yonsei University College of Medicine, Seoul, Korea.
J Digit Imaging. 2001 Dec;14(4):173-81. doi: 10.1007/s10278-001-0102-0.
The human cochlea in the inner ear is the organ of hearing. Segmentation is a prerequisite step for 3-dimensional modeling and analysis of the cochlea. It may have uses in the clinical practice of otolaryngology and neuroradiology, as well as for cochlear implant research. In this report, an interactive, semiautomatic, coarse-to-fine segmentation approach is developed on a personal computer with a real-time volume rendering board. In the coarse segmentation, parameters, including the intensity range and the volume of interest, are defined to roughly segment the cochlea through user interaction. In the fine segmentation, a regional adaptive snake model designed as a refining operator separates the cochlea from other anatomic structures. The combination of the image information and expert knowledge enables the deformation of the regional adaptive snake effectively to the cochlear boundary, whereas the real-time volume rendering provides users with direct 3-dimensional visual feedback to modify intermediate parameters and finalize the segmentation. The performance is tested using spiral computed tomography (CT) images of the temporal bone and compared with the seed point region growing with manual modification of the commercial Analyze software. Our method represents an optimal balance between the efficiency of automatic algorithm and the accuracy of manual work.
人内耳中的耳蜗是听觉器官。分割是耳蜗三维建模与分析的前提步骤。它可能在耳鼻喉科和神经放射学的临床实践以及人工耳蜗研究中有所应用。在本报告中,在配备实时容积渲染板的个人计算机上开发了一种交互式、半自动、由粗到精的分割方法。在粗分割中,通过用户交互定义包括强度范围和感兴趣体积等参数,以大致分割耳蜗。在精分割中,设计为细化算子的区域自适应蛇模型将耳蜗与其他解剖结构分离。图像信息与专家知识的结合使区域自适应蛇能够有效地变形至耳蜗边界,而实时容积渲染为用户提供直接的三维视觉反馈,以修改中间参数并完成分割。使用颞骨螺旋计算机断层扫描(CT)图像测试该方法的性能,并与商业Analyze软件手动修改的种子点区域生长法进行比较。我们的方法代表了自动算法效率与人工操作准确性之间的最佳平衡。