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Publications

Person writing with pen

Challenges for machine learning in clinical translation of big data imaging studies.

Dinsdale NK. et al, (2022), Neuron, 110, 3866 - 3881

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge.

Campello VM. et al, (2021), IEEE Trans Med Imaging, 40, 3543 - 3554

Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images.

Sundaresan V. et al, (2021), Med Image Anal, 73

Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images.

Sundaresan V. et al, (2021), Med Image Anal, 74

Brain tumour segmentation using a triplanar ensemble of U-Nets

Sundaresan V. et al, (2021)

Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images

Sundaresan V. et al, (2021)

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.

Melazzini L. et al, (2021), NeuroImage. Clinical, 30

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.

Melazzini L. et al, (2021), Neuroimage Clin, 30

Automated Detection of Candidate Subjects With Cerebral Microbleeds Using Machine Learning.

Sundaresan V. et al, (2021), Front Neuroinform, 15

Automated Detection of Candidate Subjects with Cerebral Microbleeds using Machine Learning

Sundaresan V. et al, (2021)

Automated Detection of Cerebral Microbleeds on MR images using Knowledge Distillation Framework

Sundaresan V. et al, (2021)

Integrating large-scale neuroimaging research datasets: harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets

Bordin V. et al, (2020)

Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images

Sundaresan V. et al, (2020)

Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference.

Sundaresan V. et al, (2019), Neuroimage, 185, 434 - 445

Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference.

Sundaresan V. et al, (2019), NeuroImage, 185, 434 - 445

Automated lesion segmentation with BIANCA: impact of population-level features, classification algorithm and locally adaptive thresholding

Sundaresan V. et al, (2018)

Automated characterization of the fetal heart in ultrasound images using fully convolutional neural networks

Sundaresan V. et al, (2017), Proceedings - International Symposium on Biomedical Imaging, 671 - 674

BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.

Griffanti L. et al, (2016), Neuroimage, 141, 191 - 205

Computer-assisted grading of diabetic macular edema on retinal color fundus images.

Sundaresan V. et al, (2015), Conf Proc IEEE Eng Med Biol Soc, 2015, 4330 - 4333