On the properties of the intensity-curvature measurement approaches: the signal resilient to interpolation and the resilient curvature

Ciulla, Carlo; Veljanovski, Dimitar; Shikoska, Ustijana Rechkoska; Risteski, Filip A.

doi:10.1504/ijica.2016.077595

Cited by 2 publications

(3 citation statements)

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“…2). Recent research reports on the meaning and the nature of the ICMAs showing that: (i) the CC and the ICF are filter masks (Ciulla et al, 2016c), (ii) the signal resilient to interpolation is a filter (Ciulla et al, 2016b), and (iii) the resilient curvature inverts, smooths and magnifies (all at once) the grayscale of the image (Ciulla et al, 2016b). Samples of the SRI and the RC of MRI zones of interest are presented in figures 5 and 6, and the MRIs are presented in figures 3 and 4.…”

Section: Discussionmentioning

confidence: 99%

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

Ciulla

Shikoska

Veljanovski³

et al. 2018

J. Inst. Sci. Tech.

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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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Section: Discussionmentioning

confidence: 99%

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

Ciulla

Shikoska

Veljanovski³

et al. 2018

J. Inst. Sci. Tech.

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“…The problem addressed in this paper is to devise signal processing masking techniques that make use of high-pass filtering effect of ICF, image inversion effect of RC, 51 and filtering effect of SRI 58 and CC. 57 Combining the effect of ICMAs is aimed to obtain images that emphasize on vasculature.…”

Section: Novel Contributions Of This Researchmentioning

confidence: 99%

“…The images add up to the knowledge of MRI postprocessing. The major findings 48,57,58 show that (1) SRI provides MRI with an enhanced grayscale, (2) both CC and ICF are able to create high-pass filtering effect, and (3) resilient curvature provides MRI with inverted, smoothed, and magnified grayscale.…”

Section: Related Researchmentioning

confidence: 99%

The use of the intensity‐curvature measurement approaches: Applications in magnetic resonance imaging of the human brain

Ciulla

2019

Engineering Reports

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This research describes signal processing techniques useful to highlight and contrast enhance human brain vessels detected with magnetic resonance imaging (MRI). The signal is here represented as multiplication between image intensity and the sum of second‐order partial derivatives of the model function fitted to MRI data. The implication of this novel and different concept is the introduction of the new variable called intensity‐curvature. The following six intensity‐curvature measurement approaches (ICMAs) can hence be calculated: classic‐curvature, intensity‐curvature functional (ICF), signal resilient to interpolation, resilient curvature, and intensity‐curvature terms (ICTs) before and after interpolation. This paper explores the use of ICMAs with applications in human brain MRI. Studying vasculature of the human brain is possible through two techniques apt to measure human brain MRI intensity‐curvature. The first technique is the inverse Fourier transformation procedure, which uses as k‐space filters the ICTs before and after interpolation. The other technique is called intensity‐curvature masking procedure, and it raises each ICMA to a power determining a nonlinear combination of ICMAs to sum up to MRI image intensity on a pixel‐by‐pixel basis. This paper reports that ICTs are k‐space filters, ICF is a high‐pass filter, and ICMAs are mask images. The major implication of these methodologies is effective k‐space filtering. The techniques here presented support visualization of human brain vessels. The advantage of these methods relies in speed of computation.

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On the properties of the intensity-curvature measurement approaches: the signal resilient to interpolation and the resilient curvature

Cited by 2 publications

References 61 publications

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

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

The use of the intensity‐curvature measurement approaches: Applications in magnetic resonance imaging of the human brain

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