Improved Signal and Image Interpolation in Biomedical Applications : The Case of Magnetic Resonance Imaging (MRI)

Advances have been made in improved signal and image interpolation that derive a unified framework, thus achieving improvement of the approximation properties of the interpolation function regardless of its dimensionality or degree. Improved Signal and Image Interpolation in Biomedical Applications: The Case of Magnetic Resonance Imaging (MRI) presents a novel approach for the improvement of the approximation characteristics of interpolation functions. A unique and original resource, this book approaches both the theory and methodology absent from most publications of its kind, a valuable inclusion for those interested in exploring the innovative approach that this reference proposes.

Carlo Ciulla holds the Laurea in Management Engineering (University of Palermo, Italy), the MS in Information Systems and the PhD in Computer and Information Science (NJIT, USA). Researcher at NIBH, Japan (1995-1997), he worked with Magnetoecephalography (MEG) studying the spontaneous alpha rhythm of the human brain. In the year 2000, he joined NJIT where he served as research and teaching assistant. Between the years 2002-2007 he was research associate at Yale University, postdoctoral fellow at the University of Iowa and Wayne State University. He worked on several aspects of signal processing in Magnetic Resonance Imaging (MRI), functional MR Imaging (fMRI), Perfusion Weighted Imaging (PWI), and Phase Imaging. In 2007 joined Lane College (USA) as Assistant Professor of Computer Science. His research interests relate to mathematical computational engineering: Artificial Neural Networks, Image Registration in fMRI, Signal-Image Interpolation, MEG alpha rhythm. He has authored and co-authored 15 among journal papers and conference proceedings. Also, Carlo Ciulla is the author of the book: AUTOALIGN: Methodology and Technology for the Alignment of Functional Magnetic Resonance Imaging Time Series. Image Registration: The case of Functional MRI.