Journal article
IMAGE SEGMENTATION WITH ASTEROIDALITY/TUBULARITY AND SMOOTHNESS CONSTRAINTS
International journal of computational geometry & applications, Vol.12(5), pp.413-428
10/2002
DOI: 10.1142/S0218195902000955
Abstract
Image segmentation with specific constraints has found applications in several areas such as biomedical image analysis and data mining. In this paper, we study the problem of segmenting star-shaped and smooth objects in 2-D and tubular objects in 3-D images. Image objects of these shapes are often studied in medical applications. For the 2-D case of the problem, we present an O(IJ log J) time algorithm, improving the previously best known O(IJ2M) time algorithm by a factor of [Formula: see text] time, where the size of the input 2-D image is I × J and M is the smoothness parameter with 1 ≤ M ≤ J. Our 2-D algorithm is based on a combination of dynamic programming and divide-and-conquer strategy, and on computing an optimal path in an implicitly represented graph. We also prove that a generalized version of the 3-D case of the problem is NP-hard.
Details
- Title: Subtitle
- IMAGE SEGMENTATION WITH ASTEROIDALITY/TUBULARITY AND SMOOTHNESS CONSTRAINTS
- Creators
- DANNY Z CHEN - Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USAJIE WANG - Department of Computer Science, University of Massachusetts Lowell, One University Avenue, Lowell, MA 01854, USAXIAODONG WU - Department of Computer Science, University of Texas – Pan American, 1201 West University, Edinburg, TX 78596, USA
- Resource Type
- Journal article
- Publication Details
- International journal of computational geometry & applications, Vol.12(5), pp.413-428
- DOI
- 10.1142/S0218195902000955
- ISSN
- 0218-1959
- eISSN
- 1793-6357
- Language
- English
- Date published
- 10/2002
- Academic Unit
- Electrical and Computer Engineering; Radiation Oncology
- Record Identifier
- 9984047672902771
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