On the properties of the intensity-curvature measurement approaches: the signal resilient to interpolation and the resilient curvature. (2016)

• Record Type: Journal Article
• Authors: Ciulla, Carlo; Veljanovski, Dimitar; Shikoska, Ustijana Rechkoska; Risteski, Filip A.
• Is Part Of: International journal of innovative computing and applications. Volume 7:Number 2(2016)
• Page Start: 91
• Page End: 118
• Publication Date: 2016
• Subjects: intensity-curvature measurement -- signal resilience -- interpolation -- resilient curvature -- magnetic resonance imaging -- MRI -- brain tumours -- medical images -- brain scans -- image processing; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Magnetic resonance imaging (MRI) was used to image the brain of eleven human subjects affected by tumour. The bivariate cubic Lagrange and the parametric bivariate quadratic B-Spline formulae were fitted to two-dimensional MRI images. Post-processing techniques consisting of images called intensity-curvature measurement approaches were calculated from the MRI and were used to study the brain tumours. The intensity-curvature measurement approaches were: 1) the signal resilient to interpolation (SRI); 2) the resilient curvature (RC). This work shows evidence that the SRI and the RC were able to provide information about the tumours. The evidence consisted of: 1) the capability of the signal resilient to interpolation to smooth or to illuminate the MRI; 2) the capability of the resilient curvature to provide the MRI images with inverted, smoothed and magnified greyscale, which allows observation of the tumours with fine level of details. The aforementioned evidence is the novelty presented by this paper.