25 May 1989 Mathematical Morphology for Multidimensional Image Analysis
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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 Mathematical Morphology. We propose the Generalized Morphological operators for segmentation in multidimensions. Apriori knowledge of the approximate location of the object surface is commu-nicated 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. The detected surface is represented as a hierarchical combination of patches. Initial results obtained by using the algorithm to segment the Brain from cranial MRI scans is presented.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Raj Acharya, Raj Acharya, } "Mathematical Morphology for Multidimensional Image Analysis", Proc. SPIE 1092, Medical Imaging III: Image Processing, (25 May 1989); doi: 10.1117/12.953274; https://doi.org/10.1117/12.953274

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