Home // AICT 2014, The Tenth Advanced International Conference on Telecommunications // View article
Authors:
Carlo Ciulla
Ustijana Reckoska Shikoska
Dijana Capeska Bogatinoska
Filip Risteski
Dimitar Veljanovski
Keywords: Model Function; Classic-Curvature; Intensity-Curvature Functional; Signal-Image; Magnetic Resonance Imaging (MRI); Human Brain
Abstract:
This paper intends to present a novel approach to the extraction of additional and/or complementary biomedical information from the Magnetic Resonance Imaging (MRI) of the human brain. The extraction of the biomedical information is conducted through three mathematical engineering tools called Classic-Curvature, Intensity-Curvature Functional and Intensity-Curvature Measure, which are calculated through a model function fitted to the MRI data. The mathematical engineering tools require that the model function benefits of the property of second-order differentiability. The Classic-Curvature, the Intensity-Curvature Functional and the Intensity-Curvature Measure descend from the unifying theory and the unified theory originally conceived for the improvement of the interpolation error. The advantage provided through the methodological approach is that an immense number of possible Classic-Curvature, Intensity-Curvature Functional and Intensity-Curvature Measure images can be derived through re-sampling at the intra-pixel coordinate, and this fact provides the possibility to choose images which give the best result in diagnostic practice. The biomedical information might be used in telemedicine.
Pages: 1 to 7
Copyright: Copyright (c) IARIA, 2014
Publication date: July 20, 2014
Published in: conference
ISSN: 2308-4030
ISBN: 978-1-61208-360-5
Location: Paris, France
Dates: from July 20, 2014 to July 24, 2014