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

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Ciulla, Carlo
IGI Global, Mar 31, 2009 - Computers - 640 pages
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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.

 

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Contents

Magnetic Resonance Imaging and the SignalImage Processing Techniques Developed Under the Umbrella of the Unifying Theory
1
The Intuition
23
The Conception of the IntensityCurvature Functional
31
The Conception of the SubPixel Efficacy Region
40
Assessment of the Truth Foreseen in the Intuition
48
The Notion
52
Bivariate Linear Interpolation Function
58
The Results of the SubPixel Efficacy Region Based Bivariate Linear Interpolation Function
72
On the Literature of BSpline Interpolation Functions
214
The Extension of Theory and Methodology to BSplines
223
The Results of the SubPixel Efficacy RegionBased BSpline Interpolation Functions
239
On the Properties of the Unifying Theory and the Derived SubPixel Efficacy Region
338
The Main Innovation Determined By the SubPixel Efficacy Region
348
The Unifying Theory Embraces Lagrange and Sinc Interpolation Functions
353
The Results of the SubPixel Efficacy RegionBased Lagrance and Sinc Interpolation Functions
371
On the Implications of the SubPixel Efficacy Region and the Bridging Concept of the Unifying Theory
471

Interpolation Procedures
172
The Extension of the Theory to the Trivariate Linear Interpolation Function
180
The Results of the SubPixel Efficacy Region Based Trivariate Linear Interpolation Function
188
Trivariate Linear Interpolation Function
206
Appendix
512
About the Author
612
Index
613
Copyright

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About the author (2009)

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.” [Editor]

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