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

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!

Calling Matlab (custom) functions from Python

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

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.

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.

Creation of a GitHub repository for lectures material

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

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

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.

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.

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.

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.

Recent Publications

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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 …

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 …

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