Paper
28 February 2007 GICEB: automatic segmentation algorithm for biomedical images
Author Affiliations +
Proceedings Volume 6498, Computational Imaging V; 64981I (2007) https://doi.org/10.1117/12.716208
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States
Abstract
Automatic segmentation is an essential problem in biomedical imaging. It is still an open problem to automatically segment biomedical images with complex structures and compositions. This paper proposes a novel algorithm called Gradient-Intensity Clusters and Expanding Boundaries (GICEB). The algorithm attempts to solve the problem with considerations of the image properties in intensity, gradient, and spatial coherence in the image space. The solution is achieved through a combination of using a two-dimensional histogram, domain connectivity in the image space, and segment region growing. The algorithm has been tested on some real images and the results have been evaluated.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qiqi Wang, Navaneetha Vaidhyanathan, Fijoy Vadakkumpadan, and Yinlong Sun "GICEB: automatic segmentation algorithm for biomedical images", Proc. SPIE 6498, Computational Imaging V, 64981I (28 February 2007); https://doi.org/10.1117/12.716208
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KEYWORDS
Image segmentation

Image processing algorithms and systems

Magnetic resonance imaging

Biomedical optics

Brain

Neuroimaging

Gaussian filters

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