Semiautomatic Segmentation of the Cochlea Using Real-Time Volume Rendering and Regional Adaptive Snake Modeling

Abstract

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.