This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

The intensity-curvature functional (ICF) of a model polynomial function is defined on a pixel-by-pixel basis by the ratio between the intensity-curvature term before interpolation and the intensity-curvature term after interpolation. Through the comparison with the traditional high-pass filter (HPF), this work presents evidence that the ICFs of three model polynomial functions can be tuned as HPFs. The evidence consists of the mathematical characterization of the ICF-based HPFs, qualitative comparisons in magnetic resonance imaging (MRI) of the human brain, and the determination of the finite impulse response (FIR) of the filters. The ICF-based HPFs can remove periodic noise in the low-frequency band. K E Y W O R D S finite impulse response, high-pass filter, intensity-curvature functional, model polynomial function, magnetic resonance imaging wileyonlinelibrary.com/journal/ima Int J Imaging Syst Technol.

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