Model-based segmentation for multidimensional biomedical image analysis

Raj S. Acharya

doi:10.1117/12.19550

1 May 1990 Model-based segmentation for multidimensional biomedical image analysis

Raj S. Acharya

Proceedings Volume 1245, Biomedical Image Processing; (1990) https://doi.org/10.1117/12.19550
Event: Electronic Imaging: Advanced Devices and Systems, 1990, Santa Clara, CA, United States

Abstract

One of the initial steps in the analysis of 3-D/4-D images is Segmentation, which entails partitioning the images into relevant subsets such as object and background. In this paper, we present a multidimensional segmentation algorithm to extract object surfaces from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans. The algorithm is formulated in the framework of blackboard model and uses Mathematical Morphology. We propose the Generalized Morphological operators( which are used as Knowledge Sources) for segmentation in multidimensions. Apriori knowledge of the approximate location of the object surface is communicated to the algorithm via the definition of the Search Space. The algorithm uses this definition of the Search Space to obtain the Surface Candidate elements. The search space specification reduces the computational cost and increases the reliability of the detected features.

Citation Download Citation

Raj S. Acharya "Model-based segmentation for multidimensional biomedical image analysis", Proc. SPIE 1245, Biomedical Image Processing, (1 May 1990); https://doi.org/10.1117/12.19550

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