Luigi Landini

Advanced image processing in magnetic resonance imaging

SIGNAL AND IMAGE GENERATION AND RECONSTRUCTION Basic Physics of MR Signal and Image Generation M.F. Santarelli Advanced Image Reconstruction Methods in MRI L. Ying and Z-P. Liang Parallel MRI: Concepts and Methods W.E. Kyriakos and W.S. Hoge SNR IMPROVEMENT AND INHOMOGENEITIES CORRECTION Estimation of Signal and Noise Parameters from MR Data A.J. den Dekker and J. Sijbers Retrospective Evaluation and Correction of Intensity Inhomogeneity M. Styner and K. Van Leemput Noise Filtering Methods in MRI L. Landini, M. Lombardi, and A. Benassi IMAGE PROCESSING AND QUANTITATIVE ANALYSIS Image Registration Methods in MRI V. Positano Multimodal Integration: fMRI, MRI, EEG, and MEG Y.O. Halchenko, S.J. Hanson, and B.A. Pearlmutter A Survey of Three-Dimensional Modeling Techniques for Quantitative Functional Analysis of Cardiac Images A.F. Frangi, W.J. Niessen, M.A. Viergever, and B.P.F. Lelieveldt MRI Measurement of Heart Wall Motion A.A. Young SPECTROSCOPY, DIFFUSION, ELASTICITY: FROM MODELING TO PARAMETRIC IMAGE GENERATION Principles of MR Spectroscopy and Chemical Shift Imaging U. Klose and F. Jiru Data Processing Methods in MRS L.T. Mainardi and S. Cerutti Image Processing of Diffusion Tensor MRI Data L. ODonnell, S. Haker, and C-F. Westin Analysis of Dynamic Magnetic Resonance Elastography Data A. Manduca BOLD CONTRAST MR IMAGING AND fMRI SIGNAL ANALYSIS Fundamentals of Data Analysis Methods in Functional MRI E. Formisano, F. Di Salle, and R. Goebel Exploratory Data Analysis Methods in Functional MRI N. Vanello and L. Landini Classical and Bayesian Inference in fMRI W.D. Penny and K.J. Friston Modeling and Nonlinear Analysis in fMRI via Statistical Learning Y.M. Wang Assessment of Cerebral Blood Flow, Volume, and Mean Transit Time from Bolus-Tracking MRI Images: Theory and Practice A. Bertoldo, F. Zanderigo, and C. Cobelli INDEX

Multichannel techniques for motion artifacts removal from electrocardiographic signals.

Electrocardiographic (ECG) signals are affected by several kinds of artifacts, that may hide vital signs of interest. Motion artifacts, due to the motion of the electrodes in relation to patient skin, are particularly frequent in bioelectrical signals acquired by wearable systems. In this paper we propose different approaches in order to get rid of motion confounds. The first approach we follow starts from measuring electrode motion provided by an accelerometer placed on the electrode and use this measurement in an adaptive filtering system to remove the noise present in the ECG. The second approach is based on independent component analysis methods applied to multichannel ECG recordings; we propose to use both instantaneous model and a frequency domain implementation of the convolutive model that accounts for different paths of the source signals to the electrodes

Dynamic PET Data Generation and Analysis Software Tool for Evaluating the SNR Dependence on Kinetic Parameters Estimation

In the present work, a dynamic PET data generation and analysis tool is described. It allows to analyze several factors influencing the data SNR and the consequent correctness of the pharmacokinetic parameters estimation.