Search Results for author: Yaël Balbastre

Found 11 papers, 5 papers with code

Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI

no code implementations5 Dec 2023 Sean I. Young, Yaël Balbastre, Bruce Fischl, Polina Golland, Juan Eugenio Iglesias

Here, we propose a SVR method that overcomes the shortcomings of previous work and produces state-of-the-art reconstructions in the presence of extreme inter-slice motion.

3D Reconstruction Depth Estimation +1

SuperWarp: Supervised Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration

no code implementations15 May 2022 Sean I. Young, Yaël Balbastre, Adrian V. Dalca, William M. Wells, Juan Eugenio Iglesias, Bruce Fischl

In recent years, learning-based image registration methods have gradually moved away from direct supervision with target warps to instead use self-supervision, with excellent results in several registration benchmarks.

Image Registration

Correcting inter-scan motion artefacts in quantitative R1 mapping at 7T

1 code implementation24 Aug 2021 Yaël Balbastre, Ali Aghaeifar, Nadège Corbin, Mikael Brudfors, John Ashburner, Martina F. Callaghan

Conclusion: The proposed methods simplify inter-scan motion correction of $R_1$ maps and are applicable at both 3T and 7T, where a body coil is typically not available.

An MRF-UNet Product of Experts for Image Segmentation

1 code implementation12 Apr 2021 Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

While convolutional neural networks (CNNs) trained by back-propagation have seen unprecedented success at semantic segmentation tasks, they are known to struggle on out-of-distribution data.

Image Segmentation Semantic Segmentation

Flexible Bayesian Modelling for Nonlinear Image Registration

no code implementations3 Jun 2020 Mikael Brudfors, Yaël Balbastre, Guillaume Flandin, Parashkev Nachev, John Ashburner

We describe a diffeomorphic registration algorithm that allows groups of images to be accurately aligned to a common space, which we intend to incorporate into the SPM software.

Anatomy Image Registration

Joint Total Variation ESTATICS for Robust Multi-Parameter Mapping

1 code implementation28 May 2020 Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner

Quantitative magnetic resonance imaging (qMRI) derives tissue-specific parameters -- such as the apparent transverse relaxation rate R2*, the longitudinal relaxation rate R1 and the magnetisation transfer saturation -- that can be compared across sites and scanners and carry important information about the underlying microstructure.

Groupwise Multimodal Image Registration using Joint Total Variation

1 code implementation6 May 2020 Mikael Brudfors, Yaël Balbastre, John Ashburner

In medical imaging it is common practice to acquire a wide range of modalities (MRI, CT, PET, etc.

Image Registration

Nonlinear Markov Random Fields Learned via Backpropagation

1 code implementation27 Feb 2019 Mikael Brudfors, Yaël Balbastre, John Ashburner

Although convolutional neural networks (CNNs) currently dominate competitions on image segmentation, for neuroimaging analysis tasks, more classical generative approaches based on mixture models are still used in practice to parcellate brains.

Image Segmentation Segmentation +1

Diffeomorphic brain shape modelling using Gauss-Newton optimisation

no code implementations19 Jun 2018 Yaël Balbastre, Mikael Brudfors, Kevin Bronik, John Ashburner

Shape modelling describes methods aimed at capturing the natural variability of shapes and commonly relies on probabilistic interpretations of dimensionality reduction techniques such as principal component analysis.

Dimensionality Reduction

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