Mathematical Imaging in Medicine and Neurosciences

Papers

1. 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.
2. 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
3. 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
4. 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.
5. 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
6. 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.

Posters

• 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.

Software

• Resolution calculator (Scilab)
• Lesion Segmentation (Scilab, alpha)

Presentations

1. D.Poggiali, Resolution of a Gamma camera: Analytical vs Experimental methods, CAE 2013, Pacengo del Garda VR.
2. D. Poggiali The numb3rs 0f a Br4in, Istituto per le Applicazioni del Calcolo (IAC), CNR, Rome, 04/2016.
3. D. Poggiali, MS lesion segmentation in MR image: a multithresholding approach, Ca' Foscari VE, 2014.
4. D. Poggiali, Data Analysis in MRI and PET/MRI Neuroimaging pyconIE2016, Dublin, Ireland. video link

PhD/MD theses

• Metabolismo assoluto del 18F-fdg nell'emisfero controlaterale alla lesione neoplastica mediante PET/RM: studio pre e post chirurgico, candidate: Chiara Mezzato, University of Padua, A. Y. 2016-17.
• Postprocessing Neuroimaging methods in MRI and PET/MRI with applications to Multiple Sclerosis and other Neurological diseases.,
  Davide Poggiali (2017). Advisor: E. Pegoraro. Co-advisor: P. Gallo.

Master theses

• 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.

Degree theses

• 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.