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Customized First and Second Order Statistics Based Operators to Support Advanced Texture Analysis of MRI Images
Joint Authors
Avola, Danilo
Placidi, Giuseppe
Cinque, Luigi
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-12
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Texture analysis is the process of highlighting key characteristics thus providing an exhaustive and unambiguous mathematical description of any object represented in a digital image.
Each characteristic is connected to a specific property of the object.
In some cases the mentioned properties represent aspects visually perceptible which can be detected by developing operators based on Computer Vision techniques.
In other cases these properties are not visually perceptible and their computation is obtained by developing operators based on Image Understanding approaches.
Pixels composing high quality medical images can be considered the result of a stochastic process since they represent morphological or physiological processes.
Empirical observations have shown that these images have visually perceptible and hidden significant aspects.
For these reasons, the operators can be developed by means of a statistical approach.
In this paper we present a set of customized first and second order statistics based operators to perform advanced texture analysis of Magnetic Resonance Imaging (MRI) images.
In particular, we specify the main rules defining the role of an operator and its relationship with other operators.
Extensive experiments carried out on a wide dataset of MRI images of different body regions demonstrating usefulness and accuracy of the proposed approach are also reported.
American Psychological Association (APA)
Avola, Danilo& Cinque, Luigi& Placidi, Giuseppe. 2013. Customized First and Second Order Statistics Based Operators to Support Advanced Texture Analysis of MRI Images. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-455058
Modern Language Association (MLA)
Avola, Danilo…[et al.]. Customized First and Second Order Statistics Based Operators to Support Advanced Texture Analysis of MRI Images. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-13.
https://search.emarefa.net/detail/BIM-455058
American Medical Association (AMA)
Avola, Danilo& Cinque, Luigi& Placidi, Giuseppe. Customized First and Second Order Statistics Based Operators to Support Advanced Texture Analysis of MRI Images. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-13.
https://search.emarefa.net/detail/BIM-455058
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-455058