About me
I am a Biomedical engineer born and raised in Sardinia who works in Magnetic Resonance Imaging (MRI). I graduated at the University of Cagliari (BEng Biomedical engineering, 2009) and University of Genoa (MEng Bioengineering, 2012) and then obtained a PhD at University College London (UCL) (Magnetic Resonance Physics, 2016). I have worked as a post-doc at UCL from February 2016 to September 2020, where I was a member of the Queen Square Institute of Neurology and Centre for Medical Image Computing. I keep collaborating closely with UCL, of which I am a Honorary Senior Research Associate. I have been Trainee representative (2018-2020) of the White Matter Study Group of the International Society for Magnetic Resonance in Medicine (ISMRM), of which I am a member since 2013. Since October 2020 I am a post-doc at the Vall d'Hebron Institute of Oncology (Barcelona, Spain), where I work on quantitative MRI (qMRI) development for precision medicine in cancer. In 2021 I was awarded a post-doctoral Beatriu de Pinós Fellowship by the Generalitat de Catalunya to develop novel liver diffusion MRI methods in oncological applications. From 2022, I am a "la Caixa" Foundation Junior Leader Fellow. My project, entitled "New-generation oncological MRI (New-OncoMRI): development, validationand application", aims to boost the sensitivity and biological specificity of diffusion MRI in cancer using artificial intelligence and computer simulations informed by histology.
Useful links
Link to my CV with lists of publications, grants and awards.
Link to my Google Scholar and ORCID profiles.
Link to my PhD thesis at UCL.
My code
I strongly believe in open science. I have released the following repositories:
bodymritools: tools for the processing of MRI and histological data in body imaging applications, developed as part of my "la Caixa" Fellowship. Used in Grussu et al, medrxiv 2024: 24306429.
MChepato: synthetic data and code used for the paper Grussu et al, Magn Reson Med 2022.
SARDU-Net: a command-line Python implementation of the Select And Retrieve via Direct Upsampling network (SARDU-Net) algorithm, for data-driven, model-free qMRI protocol design, presented in Grussu et al, Front Phys 2021.
qMRI-Net: a command-line Python toolbox for model fitting and qMRI resampling based on deep learning, presented in Grussu et al, Proc Comp Diff MRI 2020.
MyRelax: a collection of Python tools to perform myelin and relaxation analyses in MRI, used in Grussu et al, NeuroImage 2020.
MRItools: a collection of Python, MATLAB and Bash tools useful to handle MRI data, also used in Grussu et al, NeuroImage 2020.
StructureTensorToolbox: a structure tensor analysis toolbox for MATLAB, useful to analyse 2D histological images, used in Grussu et al, J Neurosci Meth 2016 and in Grussu et al, Ann Clin Transl Neur 2017.
PaperScripts: data and code used to write a number of papers at UCL.