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

Authors
 Sun K. Yoo  ;  Ge Wang  ;  Jay T. Rubinstein  ;  Michael W. Vannier 
Citation
 JOURNAL OF DIGITAL IMAGING, Vol.14(4) : 173-181, 2001 
Journal Title
JOURNAL OF DIGITAL IMAGING
ISSN
 0897-1889 
Issue Date
2001
MeSH
Cochlea/diagnostic imaging* ; Humans ; Image Processing, Computer-Assisted/methods* ; Imaging, Three-Dimensional ; Tomography, X-Ray Computed
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.
Files in This Item:
T200101640.pdf Download
DOI
10.1007/s10278-001-0102-0
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Medical Engineering (의학공학교실) > 1. Journal Papers
Yonsei Authors
Yoo, Sun Kook(유선국) ORCID logo https://orcid.org/0000-0002-6032-4686
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/142131
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