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Mathematical Imaging in Medicine and Neurosciences
This multidisciplinary group aims to construct new tools for Imaging and Image-derived Neurological data analysis, with focus on numerical methods and error estimation. These tool are meant to be applied in MRI, PET, SPECT imaging in clinical research or as a support for clinical practice.
People: S. De Marchi, D. Cecchin, D. Poggiali,
C. Campi, F. Marchetti and P. Gallo.
- An automated PET/CT brain segmentation for regional amyloid semi-quantification
submitted draft, with D. Poggiali, S. de Marchi, L Ruffini, P Caffarra, H. Barthel, O. Sabri, F. Bui, D. Cecchin.
- Lissajous sampling and spectral filtering in MPI applications: the reconstruction algorithm for reducing the Gibbs phenomenon F.Marchetti, S. De Marchi and W. Erb - IEEE Conference Publications - 2017 International Conference on Sampling Theory and Applications (SampTA), 580--584
- Spectral filtering for the reduction of the Gibbs phenomenon for polynomial approximation methods on Lissajous curves with applications in MPI
F.Marchetti, S. De Marchi and W. Erb - Dolomites Res. Notes Approx. 10 (2017), 128--137
- Image Reconstruction from Scattered Radon Data by Weighted Positive Definite Kernel Functions
draft, with A. Iske and G. Santin, Calcolo 55(2) (2018), https://doi.org/10.1007/s10092-018-0247-6.
- Kernel-based Image Reconstruction from Scattered Radon Data
by S. De Marchi, A. Iske and A. Sironi
Dolomites Res. Notes on Approx. Vol 9 (2016), special issue for the workshop "Kernel-based methods and function approximation", pp. 19-31.
available as Hamburger Beitraege
zur Angewandten Mathematik 2016-11
- Analytical and experimental FWHM of a gamma camera: theoretical and practical issues
D. Cecchin, D. Poggiali, L. Riccardi, P. Turco, F. Bui, S. De Marchi, PeerJ (2015), https://doi.org/10.7717/peerj.722.
- D. Poggiali, D. Cecchin, A. Favaretto, A. Lazzarotto, M. Margoni, A. Riccardi, A.C. Frigo, P. Zucchetta, F. Causin, F. Bui, P. Gallo, 3T-PET/MRI discloses different metabolic states of cortical lesions in Multiple Sclerosis, ECTRIMS 2017
- F. Marchetti Lissajous sampling and spectral filtering in MPI applications: the reconstruction algorithm for reducing the Gibbs phenomenon, SampTA 2017, Tallinn, Estonia
- F. Marchetti Spectral filtering for the resolution of the Gibbs phenomenon in MPI applications, DWCAA16
- D.Poggiali, Resolution of a Gamma camera: Analytical vs Experimental methods , DRWA13, Canazei TN.
- D.Poggiali, Resolution of a Gamma camera: Analytical vs Experimental methods, CAE 2013, Pacengo del Garda VR.
- D. Poggiali The numb3rs 0f a Br4in, Istituto per le Applicazioni del Calcolo (IAC), CNR, Rome, 04/2016.
- D. Poggiali, MS lesion segmentation in MR image: a multithresholding approach, Ca' Foscari VE, 2014.
- D. Poggiali, Data Analysis in MRI and PET/MRI Neuroimaging pyconIE2016, Dublin, Ireland. video link
- Medical image reconstruction using kernel based methods, candidate: Amos Sironi,
University of Padua, A. Y. 2010-11.
- Radial basis functions networks for ODEs: application to diabetes and insulin
therapy models, candidate: Giulia Antinori, University of Padua, A. Y. 2011-12.
- Reconstruction of medical images from Radon data in trasmission and emission
tomography, candidate: Davide Poggiali, University of Padua, A. Y. 2011-12.
- Kernel-based medical image reconstruction, candidate: Maria Angela Narduzzo,
University of Padua, A. Y. 2013-14.
- Kernel-based medical image reconstruction from Radon data, candidate: Silvia
Guglielmo, University of Padua, A. Y. 2013-14.
- Medical Image Registration for motion detection and correction, candidate: Ada Passarini, University of Padua, A. Y. 2014-15.
- Confronto tra i metodi ART e SIRT per la ricostruzione di immagini tomografiche, candidate: Giulia Nalin, University of Padua, A. Y. 2013-14.
- Semi-quantificazione del 123I-DaTSCAN: metodiche a confronto, candidate: Chiara Morbiato, University of Padua, A. Y. 2017-18.