Proceedings ArticleDOI
A fractal analysis of CT liver images for the discrimination of hepatic lesions: a comparative study
C.-P.A. Sariyanni,Pantelis A. Asvestas,George K. Matsopoulos,Konstantina S. Nikita,A. Nikita,D. Kelekis +5 more
- Vol. 2, pp 1557-1560
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TLDR
The Fuzzy C-Means algorithm is applied and it is revealed that the k-th nearest neighbour method outperforms the other methods; thus discriminating up to 93% of the normal parenchyma and up to 82%" of the hepatocellular carcinoma, correctly.Abstract:
A quantitative study for the discrimination of different hepatic lesions is presented in this paper. The study is based on the fractal analysis of CT liver images in order to estimate their fractal dimension and to differentiate normal liver parenchyma from hepatocellular carcinoma. Four fractal dimension estimators have been implemented throughout this work; three well-established methods and a novel implementation of a method. Analytically, these methods correspond to the power spectrum method, the box counting method, the morphological fractal estimator and the novel modification of the kth-nearest neighbour method. The Fuzzy C-Means algorithm is finally applied revealing that the k-th nearest neighbour method outperforms the other methods; thus discriminating up to 93% of the normal parenchyma and up to 82% of the hepatocellular carcinoma, correctly.read more
Citations
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Journal ArticleDOI
Orthogonal Moments Based Texture Analysis of CT Liver Images
TL;DR: A statistical significance test has been performed to select the best moment orders to discriminate normal and abnormal tissues in liver images and the experimental results reveal the efficacy of the proposed features.
Journal Article
Texture characterization for hepatic tumor recognition in multiphase CT
TL;DR: In this article, a new approach to texture characterization from Dynamic CT scans of the liver is presented, where images with the same slice position and correspond to three typical acquisition phases are analyzed simultaneously.
Book ChapterDOI
Morphological Texture Description of Grey-Scale and Color Images
Erchan Aptoula,Sébastien Lefèvre +1 more
TL;DR: This chapter focuses on morphological texture description methods for grey-scale and color images in an effort to spread the advantages of this framework in the context of texture analysis.
Book ChapterDOI
Diagnostic Support Systems and Computational Intelligence: Differential Diagnosis of Hepatic Lesions from Computed Tomography Images
TL;DR: This chapter provides a brief overview of the use of computational intelligence methods in the design and development of DSSs aimed at the differential diagnosis of hepatic lesions from Computed Tomography images.
Medical Image Segmentation Using CT Scans-A Level Set Approach
TL;DR: A simple and clinically useful system has been developed for segmenting the liver tumor from CT images that could clearly segment the tumor regions and their boundaries are well defined.
References
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TL;DR: This book is a blend of erudition, popularization, and exposition, and the illustrations include many superb examples of computer graphics that are works of art in their own right.
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Journal ArticleDOI
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