Web proceedings papers



The intensity-curvature measurement approaches (ICMAs) are: (i) the classic-curvature (CC); (ii) the intensity-curvature functional (ICF); (iii) the signal resilient to interpolation (SRI); and (iv) the resilient curvature (RC). Even though, the ICMAs can be calculated using a wide array of model polynomial functions fitted to the image data, this paper uses selected polynomials on the basis of previous experience. After the inception, the ICMAs have been used for the study of human brain tumors imaged with Magnetic Resonance Imaging (MRI). The aforementioned study has brought to the attention the meaning and the nature of the ICMAs signal processing techniques. The CC and the ICF were discovered to act as they were high pass filtered signals. The SRI was discovered to act as a filter and it yields the property to smooth or to illuminate the image data. The RC is capable to invert, smooth and magnify the gray scale of the image data. This paper makes a summary on the meaning and the nature of the ICMAs while presenting results obtained through the use of biomedical data and also theoretical images. The novelty of this paper consists in the evidence that the Fourier domains of CC and ICF are different from those of the high pass filtered signal. An additional novelty consists in the validation of the CC and the ICF when processing theoretical images which yields to the same behavior seen when processing MRI of the human brain. Moreover, this paper confirms on the meaning and the nature of the SRI and RC.


classic-curvature, CC, intensity-curvature functional, ICF, signal resilient to interpolation, SRI, resilient curvature, RC, intensity-curvature measurement approaches, ICMAs.