標題: A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform
作者: Wu, T. Y.
Lin, S. F.
電機工程學系
Department of Electrical and Computer Engineering
關鍵字: Parotid;CT image;stationary wavelet transform;image segmentation;active contour
公開日期: 2013
摘要: Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.
URI: http://hdl.handle.net/11536/22900
http://dx.doi.org/10.2478/msr-2013-0036
ISSN: 1335-8871
DOI: 10.2478/msr-2013-0036
期刊: MEASUREMENT SCIENCE REVIEW
Volume: 13
Issue: 5
起始頁: 237
結束頁: 247
顯示於類別:期刊論文


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