The Properties of The Intensity-Curvature Measurement Approaches: Applications In Magnetic Resonance Imaging of The Human Brain

Authors

  • Carlo Ciulla University of Information Science & Technology, “St. Paul the Apostle
  • Ustijana Rechkoska Shikoska University of Information Science & Technology, “St. Paul the Apostle
  • Dimitar Veljanovski Department of Radiology, General Hospital 8-mi Septemvri, Boulevard
  • Filip A. Risteski Department of Radiology, General Hospital 8-mi Septemvri, Boulevard

DOI:

https://doi.org/10.3126/jist.v22i2.19591

Keywords:

Classic-curvature, Intensity-curvature, Resilient curvature, MRA, Arterial spin-labeling

Abstract

The intensity-curvature measurement approaches (ICMAs) are re-sampling techniques. The intensity-curvature term is the product between the signal intensity and the classic-curvature and is the root concept at the foundation of the ICMAs. The concept offers six ICMAs: the classic-curvature (CC), the intensity-curvature functional (ICF), the signal resilient to interpolation (SRI), the resilient curvature (RC), the intensity-curvature term before interpolation (Eo(x, y)), and the intensity-curvature term after interpolation (EIN(x, y)). The ICMAs have the following properties. The CC and the ICF are mask images. The SRI is a filter. The RC is adept to invert, and simultaneously, to smooth and to magnify the grayscale of the image. The aforementioned properties are illustrated with two-dimensional theoretical images and with Magnetic Resonance Imaging (MRI) images of the human brain. The novelty of this work consists of the use of the Eo(x, y) and the EIN(x, y) in order to highlight human brain vessels identified with MRI.

 Journal of Institute of Science and Technology

Volume 22, Issue 2, January 2018, Page: 19-31

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Published

2018-04-09

How to Cite

Ciulla, C., Shikoska, U. R., Veljanovski, D., & Risteski, F. A. (2018). The Properties of The Intensity-Curvature Measurement Approaches: Applications In Magnetic Resonance Imaging of The Human Brain. Journal of Institute of Science and Technology, 22(2), 19–31. https://doi.org/10.3126/jist.v22i2.19591

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Section

Research Articles