About me

I am a Postdoctoral Research Fellow at the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and Harvard Medical School, working in Ciprian Catana‘s PET-MR lab.

My main research interest is on tomographic image reconstruction and parametric maps estimation from PET data. I am an author of several peer-reviewed publications and proceedings, mainly on: models for 4D PET image reconstruction incorporating kinetic modeling and clustering; strategies for improving maps’ SNR and accelerating voxelwise fitting via GPU parallelization; PET reconstruction algorithms for non-Poisson data.

Interests

  • Machine learning
  • Parallel programming
  • CUDA
  • Positron Emission Tomography (PET)
  • Kinetic modeling

Education

  • Ph.D. in Biomedical Engineering, 2018

    University of Pisa - Pisa (IT)

  • M.Sc. in Biomedical Engineering, 2015

    University of Pisa - Pisa (IT)

  • BSc in Biomedical Engineering, 2011

    Università Politecnica delle Marche - Ancona (IT)

Recent Posts

Feb 11, 2019 2 min read

Add comments to your Hugo-Academic blog in 10 minutes, using Utteranc.es

A lightweight comments widget built on GitHub issues. Use GitHub issues for blog comments!

Feb 5, 2019 12 min read

Calling Matlab (custom) functions from Python

Different strategies to call and use matlab scripts and functions from Python code.

Nov 16, 2017 4 min read

Exending MATLAB's tools for Negative Binomial distributions: nbin*_mu.m

Introducing a new set of functions able to deal with the common µ-k parametrization of the Negative Binomial distribution for count data.

Nov 15, 2017 1 min read

Changelog for KMtoolbox repository - November 14, 2017

Kinetic Modeling Toolbox designed to estimate kinetic parameters from 4D PET and DCE-MRI dataset at a ROI level.

Nov 14, 2017 1 min read

Creation of a GitHub repository for lectures material

Introduction of the new repository and list of lectures material organized by year.

See all posts

Projects

MATLAB toolbox: nbin*_mu

This repo is about adding the missing µ-k parametrization for the Negative Binomial (NB) distribution in Matlab.

CUDA-GPU kinetic modeling

GPU-LMfit - Python/CUDA library for parallel fitting of compartmental models to 4D medical imaging volumes.

Occiput.io

Open source tomographic reconstruction software for 2D, 3D and 4D PET, PET-MRI and SPECT, in Python using GPUs.

KMtool: Kinetic Modeling Toolbox

Kinetic Modeling Toolbox designed to estimate kinetic parameters from 4D PET and DCE-MRI dataset at a ROI level.

Recent & Upcoming Talks

Introduction to Matlab

Why & How Seminar Series, recorded 12 March 2020 This invited talk was part of a series of seminars organized by the Athinoula A. Martinos Center for Biomedical Imaging, and curated by Valeria Barletta, Avery Berman, Aina Frau-Pascual, and Mainak Jas
Mar 13, 2020 10:04 PM
Slides

Direct 4D PET reconstruction with discrete tissue types

Abstract Dynamic positron emission tomography (dPET) is known for its ability to extract spatiotemporal information of a radio tracer in living tissue. In this paper, a novel direct reconstruction framework is presented, which include concurrent clustering as a potential aid in addressing high levels of noise typical of voxel-wise kinetic modeling.
Jul 26, 2019 12:00 AM Berlin, Germany
PDF Slides

Kinetic Compressive Sensing

Introduction Parametric images provide insight into the spatial distribution of physiological parameters, but they are often extremely noisy, due to low SNR of tomographic data. Direct estimation from projections allows accurate noise modeling, improving the results of post-reconstruction fitting.
Oct 26, 2017 12:00 AM Atlanta, GA, USA
PDF Slides

Kinetic compressive sensing: improving image reconstruction and parametric maps

Introduction Parametric images provide insight into the spatial distribution of physiological parameters, but they are often extremely noisy, due to low SNR of tomographic data. Direct estimation from projections allows accurate noise modeling, improving the results of post-reconstruction fitting.
May 25, 2017 12:00 AM Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA
Slides

The Influence of Noise in Dynamic PET Direct Reconstruction

Abstract In the present work a study is carried out in order to assess the efficiency of the direct reconstruction algorithms on noisy dynamic PET data. The study is performed via Monte Carlo simulations of a uniform cylindrical phantom whose emission values change in time according to a kinetic law.
Apr 2, 2016 12:00 AM Paphos, Cyprus
PDF Slides
See all talks

Recent Publications

Quickly discover relevant content by filtering publications.

Negative binomial maximum likelihood expectation maximization (NB-MLEM) algorithm for reconstruction of pre-corrected PET data

Purpose Positron emission tomography (PET) image reconstruction is usually performed using maximum likelihood (ML) iterative …

Direct 4D PET reconstruction with discrete tissue types

Dynamic positron emission tomography (dPET) is known for its ability to extract spatiotemporal information of a radio tracer in living …
PDF

Probabilistic Graphical Models for dynamic PET: a novel approach to direct parametric map estimation and image reconstruction

In the context of dynamic emission tomography, the conventional processing pipeline consists of independent image reconstruction of …

Kinetic Compressive Sensing

Parametric images provide insight into the spatial distribution of physiological parameters, but they are often extremely noisy, due to …
PDF

Concurrent Respiratory Motion Correction of Abdominal PET and Dynamic Contrast-Enhanced–MRI Using a Compressed Sensing Approach

We present an approach for concurrent reconstruction of respiratory motion–compensated abdominal dynamic contrast-enhanced (DCE)–MRI …
PDF
See all publications

Teaching Experience

Why & How series - Introduction to MATLAB (for non-CS people!)

Athinoula A. Martinos Center for Biomedical Imaging - Boston MA, USA Mar 2020
Download the PDF version of the lecture

XXXXXXXXX

Fondazione CNR/Regione Toscana ‘G. Monasterio’ - Pisa, Italy Jun 2019

Teaching Assistant - Master of Science in Biomedical Engineering

University of Pisa - School of Engineering Nov 2018
Topics covered:

  • Iterative reconstruction techniques for emission tomography imaging: ML-EM, OS-EM, and MAP-OSL-EM
  • Introduction to kinetic modeling for emission tomography: focus on compartmental models (meaning, use, and interpratation)

Teaching Assistant - Master of Science in Biomedical Engineering

University of Pisa - School of Engineering Nov 2017

Topics covered:

Teaching Assistant - Master of Science in Biomedical Engineering

University of Pisa - School of Engineering Nov 2016

Topics covered:

Popular Topics

academic compartmental models contrast enhanced mri DCE-MRI dicom distribution emission tomography hugo kinetic modeling matlab medical imaging NB Negative Binomial optimization PET probability python scipy software tutorial

Contact