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- W2473048861 abstract "This paper is a study on texture analysis of Computer Tomography (CT) liver images using orthogonal moment features. Orthogonal moments are used as image feature representation in many applications like invariant pattern recognition of images. Orthogonal moments are proposed here for the diagnosis of any abnormalities on the CT images. The objective of the proposed work is to carry out the comparative study of the performance of orthogonal moments like Zernike, Racah and Legendre moments for the detection of abnormal tissue on CT liver images. The Region of Interest (ROI) based segmentation and watershed segmentation are applied to the input image and the features are extracted with the orthogonal moments and analyses are made with the combination of orthogonal moment with segmentation that provides better accuracy while detecting the tumor. This computational model is tested with many inputs and the performance of the orthogonal moments with segmentation for the texture analysis of CT scan images is computed and compared." @default.
- W2473048861 created "2016-07-22" @default.
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- W2473048861 date "2016-01-01" @default.
- W2473048861 modified "2023-09-29" @default.
- W2473048861 title "A Simple Computational Approach for the Texture Analysis of CT Scan Images Using Orthogonal Moments" @default.
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- W2473048861 doi "https://doi.org/10.4236/cs.2016.78163" @default.
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