Yael Balbastre

Newton International Fellow at University College London

I work on various aspects of medical image computing, with a focus on neuroimaging. I am particularly interested in generative probabilistic models, and how they can be integrated with machine learning techniques. I have worked, among other things, on Bayesian shape modelling, image segmentation and registration, and quantitative MRI. Recently, I have focused on multimodal image registration and vasculature segmentation, with the aim of building cellular-resolution atlases of the human brain.

Before (re)joining University College London (UCL), I was a faculty member at the Massachusetts General Hospital (MGH) and Harvard Medical School (HMS). Previously, I was a postdoctoral fellow with Bruce Fischl at MGH/HMS, and with John Ashburner and Martina Callaghan at UCL. I completed my PhD at the French Alternative Energies and Atomic Energy Commission (CEA), in the MIRCen and NeuroSpin laboratories, advised by Thierry Delzescaux and Jean-François Mangin.

news

Mar 01, 2024 I am starting a new adventure at University College London as a Newton International Fellow, where I will work on High-resolution spatiotemporal models of the brain across the lifespan for diagnosis and decision-making.
Feb 26, 2024 Sean’s paper on “Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI” was accepted at CVPR 2024!
Jan 16, 2024 We have a website!

selected publications

  1. arXiv
    Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI
    Sean I YoungYaël BalbastreBruce Fischl ,  Polina Golland , and 1 more author
    arXiv preprint arXiv:2312.03102, 2023
  2. Sci.Adv.
    A cellular resolution atlas of Broca’s area
    Irene Costantini ,  Leah Morgan ,  Jiarui YangYael Balbastre , and 35 more authors
    Science Advances, 2023
  3. MRM
    Correcting inter-scan motion artifacts in quantitative R1 mapping at 7T
    Yaël Balbastre ,  Ali Aghaeifar ,  Nadège Corbin ,  Mikael Brudfors , and 2 more authors
    Magnetic Resonance in Medicine, 2022
  4. MedIA
    Model-based multi-parameter mapping
    Yaël BalbastreMikael Brudfors ,  Michela Azzarito ,  Christian Lambert , and 2 more authors
    Medical Image Analysis, 2021
  5. MedIA
    An algorithm for learning shape and appearance models without annotations
    John AshburnerMikael Brudfors ,  Kevin Bronik ,  and  Yael Balbastre
    Medical image analysis, 2019