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Medical Image Analysis Through A Texture Based Computer Aided Diagnosis Framework
Danilo Avola, Luigi Cinque, Giuseppe Placidi
Pages - 144 - 152     |    Revised - 15-09-2012     |    Published - 24-10-2012
Volume - 6   Issue - 5    |    Publication Date - October 2012  Table of Contents
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KEYWORDS
Texture Analysis, Medical Imaging, Pattern Recognition, Feature Extraction, Segmentation
ABSTRACT
Current medical imaging scanners allow to obtain high resolution digital images with a complex informative content expressed by the textural aspect of the membranes covering organs and tissues (hereinafter objects). These textural information can be exploited to develop a descriptive mathematical model of the objects to support heterogeneous activities within medical field. This paper presents a framework based on the texture analysis to model the objects contained in the layout of diagnostic images. By each specific model, the framework automatically also defines a connected application supporting, on the related objects, different fixed targets, such as: segmentation, mass detection, reconstruction, and so on. The framework is tested on MRI images and results are reported.
CITED BY (3)  
1 Placidi, G., Avola, D., Petracca, A., Spezialetti, M., Cinque, L., & Levialdi, S. Novel Approches in Image Processing (IP) and Human Centred Systems (HCSs).
2 Nair, V. V., & Thushana, Y. S. (2013). Texture features from Chaos Game Representation Images of Genomes. International Journal of Image Processing (IJIP), 7(2), 183.
3 Avola, D., Cinque, L., & Placidi, G. (2013). Customized First and Second Order Statistics Based Operators to Support Advanced Texture Analysis of MRI Images. Computational and mathematical methods in medicine, 2013.
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Mr. Danilo Avola
Dept. of Life, Health and Environmental Sciences - Italy
danilo.avola@univaq.it
Professor Luigi Cinque
Sapienza University of Rome - Italy
Miss Giuseppe Placidi
Dept. of Life, Health and Environmental Sciences - Italy