Segmentation of Regions of Interest Using Active Contours with SPF Functionopen access
- Authors
- Akram, Farhan; Kim, Jeong Heon; Lee, Chan-Gun; Choi, Kwang Nam
- Issue Date
- May-2015
- Publisher
- HINDAWI PUBLISHING CORPORATION
- Citation
- COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, v.2015
- Journal Title
- COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
- Volume
- 2015
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/11388
- DOI
- 10.1155/2015/710326
- ISSN
- 1748-670X
1748-6718
- Abstract
- Segmentation of regions of interest is a well-known problem in image segmentation. This paper presents a region-based image segmentation technique using active contours with signed pressure force (SPF) function. The proposed algorithm contemporaneously traces high intensity or dense regions in an image by evolving the contour inwards. In medical image modalities these high intensity or dense regions refer to tumor, masses, or dense tissues. The proposed method partitions an image into an arbitrary number of subregions and tracks down salient regions step by step. It is implemented by enforcing a new region-based SPF function in a traditional edge-based level set model. It partitions an image into subregions and then discards outer subregion and partitions inner region into two more subregions; this continues iteratively until a stopping condition is fulfilled. A Gaussian kernel is used to regularize the level set function, which not only regularizes it but also removes the need of computationally expensive reinitialization. The proposed segmentation algorithm has been applied to different images in order to demonstrate the accuracy, effectiveness, and robustness of the algorithm.
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Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
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