Computational Intelligence in Magnetic Resonance Imaging of the Human Brain: The Classic-Curvature and the Intensity-Curvature Functional in a Tumor Case Study

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Author(s)

Carlo Ciulla 1,* Dijana Capeska Bogatinoska 1 Filip A. Risteski 2 Dimitar Veljanovski 2

1. University for Information Science & Technology, “St. Paul the Apostle”, Partizanska B.B., 6000 Ohrid, Macedonia

2. Skopje City General Hospital, Pariska B.B., 1000 Skopje, Macedonia

* Corresponding author.

DOI: https://doi.org/10.5815/ijieeb.2014.02.01

Received: 5 Jan. 2014 / Revised: 11 Feb. 2014 / Accepted: 1 Mar. 2014 / Published: 8 Apr. 2014

Index Terms

Classic-Curvature, Computational Intelligence, Intensity-Curvature Functional, Magnetic Resonance Imaging (MRI), Model Polynomial Function, Second-Order Derivative, Second-Order Differentiability

Abstract

This research solves the computational intelligence problem of devising two mathematical engineering tools called Classic-Curvature and Intensity-Curvature Functional. It is possible to calculate the two mathematical engineering tools from any model polynomial function which embeds the property of second-order differentiability. This work presents results obtained with bivariate and trivariate cubic Lagrange polynomials. The use of the Classic-Curvature and the Intensity-Curvature Functional can add complementary information in medical imaging, specifically in Magnetic Resonance Imaging (MRI) of the human brain.

Cite This Paper

Carlo Ciulla, Dijana Capeska Bogatinoska, Filip A. Risteski, Dimitar Veljanovski, "Computational Intelligence in Magnetic Resonance Imaging of the Human Brain: The Classic-Curvature and the Intensity-Curvature Functional in a Tumor Case Study", International Journal of Information Engineering and Electronic Business(IJIEEB), vol.6, no.2, pp.1-8, 2014. DOI:10.5815/ijieeb.2014.02.01

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