NDLI: Parametric mapping model for bladder using free-form deformation

Content Provider	IEEE Xplore Digital Library
Author	Yikai Zhao Yang Liu Jun Feng Hongbing Lu
Copyright Year	2013
Description	Author affiliation: Dept. of Biomed. Eng., Fourth Mil. Med. Univ., Xi'an, China (Yang Liu; Hongbing Lu) \|\| Coll. of Inf. & Technol., North West Univ., Xi'an, China (Yikai Zhao; Jun Feng)
Abstract	Virtual Endoscopy is a perspective tool for noninvasive tumor detection inside the bladder compared with optical endoscopy. Since the shape, size, position, and relations of a bladder are dependent on the amount of urine, the body position and the age of the person, it would be difficult to compare morphological or intensity features of patient's bladder at different filling stages or bladders with patients for abnormalities detection. In this paper, we present a parametric $R^{3}$ to $R^{3}$ mapping model to normalize the bladders with diverse geometric shapes of different size using Free-Form Deformation (FFD). After the establishment of an adaptive FFD to a specified bladder, various image features, such as original morphological and textural attributes of the bladder, are projected onto the model surface and then are further mapped to a Generalized Gaussian sphere. In this way, the proposed method provides a unified way to evaluate the entire bladder wall. The experimental results based on MRI data indicate the feasibility of the bladder mapping using the proposed model. From the surface of the mapped model, the thickness of the bladder can be observed clearly. Moreover, thickened regions which reflect the tumor locations are quantified and detected more easily.
Starting Page	1
Ending Page	4
File Size	334987
Page Count	4
File Format	PDF
e-ISBN	9781479905348
DOI	10.1109/NSSMIC.2013.6829364
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-10-27
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bladder Deformable models Surface morphology Mathematical model Data models Parametric statistics Shape
Content Type	Text
Resource Type	Article

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