Simone Saitta

Vision

I develop data-driven methods to make cardiovascular imaging more quantitative and objective. My work brings together deep learning, computational modeling, physics, and image analysis to support diagnosis, treatment planning, and image-guided cardiovascular procedures.

About me

I am an Assistant Professor in Cardiovascular Image Analysis at Department of Biomedical Engineering and Physics of Amsterdam UMC and affiliated to the Informatics Institute of the University of Amsterdam, where I am part of the qurAI group. I lead the technical developments of the CARA Lab, which develops robust, real-time AI for intracoronary optical coherence tomography (OCT) at the catheterization laboratory, and I contribute to the group’s Cardiovascular Lab. My current research centres on AI methods to support interventional cardiology, with an emphasis on coronary artery and aortic diseases.

More broadly, I am motivated by real clinical problems and enjoy combining ideas from machine learning, computational fluid dynamics, image analysis, and differential geometry. Recurring themes in my work include convolutional and graph neural networks for 3D medical image segmentation and surrogate modelling, implicit neural representations for imaging denoising and super-resolution, and automated pipelines for surgical and interventional pre-procedural planning.

Background

I obtained my PhD in Bioengineering (cum laude) at Politecnico di Milano in 2023, with a thesis on data-driven approaches for quantifying complex biomarkers from medical imaging, and continued there as a postdoctoral fellow and junior assistant professor before moving to Amsterdam in 2024. During my PhD I was a visiting researcher in the Cambridge Image Analysis Group at the University of Cambridge, working on inverse problems for flow-encoded MRI.

Earlier, I worked with the Biofluids and Transport Group at Imperial College London — first for my MSc thesis and then as a Research Assistant — where I built flow4D, a small tool for analysing 4D flow MR images. I also spent time as a Research Engineer in the Cardiovascular Biomechanics and Ultrasound Laboratory at the National University of Singapore, working on simulation and registration of 4D fetal heart echocardiography.

news

Jul 16, 2026	I was awarded an NWO Veni grant (TTW) for my project on probabilistic digital twins for anatomical and functional assessment of the coronary arteries — 3D coronary anatomy and hemodynamics with uncertainty quantification from single-view X-ray angiography.
Mar 31, 2026	Our CARA Lab study on uncertainty quantification for AI-based intracoronary OCT segmentation — led by Leah Heil — was accepted as a poster at ISBI 2026.
Sep 12, 2025	Our PECTUS-AI study — AI-based identification of rupture-prone coronary plaques (thin-cap fibroatheromas) and their link to clinical outcomes — is published in the European Heart Journal.
Sep 1, 2025	Our benchmark of geometric deep-learning models for learning hemodynamic scalar fields on coronary artery meshes is published in Computers in Biology and Medicine.
Jul 1, 2025	World of Forms — deformable geometric templates for one-shot surface meshing in coronary CT angiography — is out in Medical Image Analysis.

selected publications

Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI

Simone Saitta, Marcello Carioni, Subhadip Mukherjee, Carola-Bibiane Schönlieb, and Alberto Redaelli

Computer Methods and Programs in Biomedicine, 2024

Bib HTML

@article{saitta2024implicit,
  title = {Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI},
  author = {Saitta, Simone and Carioni, Marcello and Mukherjee, Subhadip and Sch{\"o}nlieb, Carola-Bibiane and Redaelli, Alberto},
  journal = {Computer Methods and Programs in Biomedicine},
  volume = {246},
  pages = {108057},
  year = {2024},
  publisher = {Elsevier},
  doi = {10.1016/j.cmpb.2024.108057},
}

A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning

Simone Saitta, Francesco Sturla, Riccardo Gorla, Omar A Oliva, Emiliano Votta, Francesco Bedogni, and Alberto Redaelli

Computers in Biology and Medicine, 2023

Bib HTML

@article{saitta2023ct,
  title = {A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning},
  author = {Saitta, Simone and Sturla, Francesco and Gorla, Riccardo and Oliva, Omar A and Votta, Emiliano and Bedogni, Francesco and Redaelli, Alberto},
  journal = {Computers in Biology and Medicine},
  volume = {163},
  pages = {107147},
  year = {2023},
  publisher = {Elsevier},
  doi = {10.1016/j.compbiomed.2023.107147},
}

Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta

Simone Saitta, Ludovica Maga, Chlöe Armour, Emiliano Votta, Declan P O’Regan, M Yousuf Salmasi, Thanos Athanasiou, Jonathan W Weinsaft, and 3 more authors

Computer Methods and Programs in Biomedicine, 2023

Bib HTML

@article{saitta2023data,
  title = {Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta},
  author = {Saitta, Simone and Maga, Ludovica and Armour, Chl{\"o}e and Votta, Emiliano and O'Regan, Declan P and Salmasi, M Yousuf and Athanasiou, Thanos and Weinsaft, Jonathan W and Xu, Xiao Yun and Pirola, Selene and Redaelli, Alberto},
  journal = {Computer Methods and Programs in Biomedicine},
  volume = {233},
  pages = {107468},
  year = {2023},
  publisher = {Elsevier},
  doi = {10.1016/j.cmpb.2023.107468},
}

A deep learning-based and fully automated pipeline for thoracic aorta geometric analysis and planning for endovascular repair from computed tomography

Simone Saitta, Francesco Sturla, Alessandro Caimi, Alessandra Riva, Maria Chiara Palumbo, Giovanni Nano, Emiliano Votta, Alessandro Della Corte, and 4 more authors

Journal of Digital Imaging, 2022

Bib HTML

@article{saitta2022deep,
  title = {A deep learning-based and fully automated pipeline for thoracic aorta geometric analysis and planning for endovascular repair from computed tomography},
  author = {Saitta, Simone and Sturla, Francesco and Caimi, Alessandro and Riva, Alessandra and Palumbo, Maria Chiara and Nano, Giovanni and Votta, Emiliano and Della Corte, Alessandro and Glauber, Mattia and Chiappino, Dante and Marrocco-Trischitta, Massimiliano M and Redaelli, Alberto},
  journal = {Journal of Digital Imaging},
  volume = {35},
  number = {2},
  pages = {226--239},
  year = {2022},
  publisher = {Springer},
  doi = {10.1007/s10278-021-00535-1},
}

Evaluation of 4D flow MRI-based non-invasive pressure assessment in aortic coarctations

Simone Saitta, Selene Pirola, Filippo Piatti, Emiliano Votta, Federico Lucherini, Francesca Pluchinotta, Mario Carminati, Massimo Lombardi, and 5 more authors

Journal of Biomechanics, 2019

Bib HTML

@article{saitta2019evaluation,
  title = {Evaluation of 4D flow MRI-based non-invasive pressure assessment in aortic coarctations},
  author = {Saitta, Simone and Pirola, Selene and Piatti, Filippo and Votta, Emiliano and Lucherini, Federico and Pluchinotta, Francesca and Carminati, Mario and Lombardi, Massimo and Geppert, Christian and Cuomo, Federica and Figueroa, Carlos Alberto and Xu, Xiao Yun and Redaelli, Alberto},
  journal = {Journal of Biomechanics},
  volume = {94},
  pages = {13--21},
  year = {2019},
  publisher = {Elsevier},
  doi = {10.1016/j.jbiomech.2019.07.004},
}