Vaanathi Sundaresan

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 19

Top Topics

Classification Algorithm

Cardiac Magnetic Resonance

Automated Detection

Top Venues

Frontiers Neuroinformatics

Publications

Vaanathi Sundaresan, Christoph Arthofer, Giovanna Zamboni, Andrew G. Murchison, Robert A. Dineen, Peter M. Rothwell, Dorothee P. Auer, Chaoyue Wang, Karla L. Miller, Benjamin C. Tendler, Fidel Alfaro-Almagro, Stamatios N. Sotiropoulos, Nikola Sprigg, Ludovica Griffanti, Mark Jenkinson
Automated detection of cerebral microbleeds on MR images using knowledge distillation framework. Frontiers Neuroinformatics 17 (2023)
Shreyas H. Ramananda, Vaanathi Sundaresan
Class Activation Map-based Weakly supervised Hemorrhage Segmentation using Resnet-LSTM in Non-Contrast Computed Tomography images. CoRR (2023)
Vaanathi Sundaresan, Julia F. Lehman, Sean P. Fitzgibbon, Saâd Jbabdi, Suzanne N. Haber, Anastasia Yendiki
Constrained Self-supervised Method with Temporal Ensembling for Fiber Bundle Detection on Anatomic Tracing Data. MOVI@MICCAI (2022)
Vaanathi Sundaresan, Nicola K. Dinsdale, Mark Jenkinson, Ludovica Griffanti
Omni-Supervised Domain Adversarial Training for White Matter Hyperintensity Segmentation in the UK Biobank. ISBI (2022)
Vaanathi Sundaresan, Julia F. Lehman, Sean P. Fitzgibbon, Saâd Jbabdi, Suzanne N. Haber, Anastasia Yendiki
Constrained self-supervised method with temporal ensembling for fiber bundle detection on anatomic tracing data. CoRR (2022)
Vaanathi Sundaresan, Christoph Arthofer, Giovanna Zamboni, Robert A. Dineen, Peter M. Rothwell, Stamatios N. Sotiropoulos, Dorothee P. Auer, Daniel J. Tozer, Hugh S. Markus, Karla L. Miller, Iulius Dragonu, Nikola Sprigg, Fidel Alfaro-Almagro, Mark Jenkinson, Ludovica Griffanti
Automated Detection of Candidate Subjects With Cerebral Microbleeds Using Machine Learning. Frontiers Neuroinformatics 15 (2021)
Víctor M. Campello, Polyxeni Gkontra, Cristian Izquierdo, Carlos Martín-Isla, Alireza Sojoudi, Peter M. Full, Klaus H. Maier-Hein, Yao Zhang, Zhiqiang He, Jun Ma, Mario Parreño, Alberto Albiol, Fanwei Kong, Shawn C. Shadden, Jorge Corral Acero, Vaanathi Sundaresan, Mina Saber, Mustafa A. Alattar, Hongwei Li, Bjoern H. Menze, Firas Khader, Christoph Haarburger, Cian M. Scannell, Mitko Veta, Adam Carscadden, Kumaradevan Punithakumar, Xiao Liu, Sotirios A. Tsaftaris, Xiaoqiong Huang, Xin Yang, Lei Li, Xiahai Zhuang, David Viladés, Martín Luís Descalzo, Andrea Guala, Lucia La Mura, Matthias G. Friedrich, Ria Garg, Julie Lebel, Filipe Henriques, Mahir Karakas, Ersin Çavus, Steffen E. Petersen, Sergio Escalera, Santi Seguí, José F. Rodríguez Palomares, Karim Lekadir
Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge. IEEE Trans. Medical Imaging 40 (12) (2021)
Vaanathi Sundaresan, Ludovica Griffanti, Mark Jenkinson
Brain tumour segmentation using a triplanar ensemble of U-Nets. CoRR (2021)
Vaanathi Sundaresan, Giovanna Zamboni, Nicola K. Dinsdale, Peter M. Rothwell, Ludovica Griffanti, Mark Jenkinson
Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images. Medical Image Anal. 74 (2021)
Vaanathi Sundaresan, Giovanna Zamboni, Peter M. Rothwell, Mark Jenkinson, Ludovica Griffanti
Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images. Medical Image Anal. 73 (2021)
Nicola K. Dinsdale, Emma Bluemke, Vaanathi Sundaresan, Mark Jenkinson, Stephen M. Smith, Ana I. L. Namburete
Challenges for machine learning in clinical translation of big data imaging studies. CoRR (2021)
Valentina Bordin, Ilaria Bertani, Irene Mattioli, Vaanathi Sundaresan, Paul McCarthy, Sana Suri, Eniko Zsoldos, Nicola Filippini, Abda Mahmood, Luca Melazzini, Maria Marcella Laganà, Giovanna Zamboni, Archana Singh-Manoux, Mika Kivimäki, Klaus P. Ebmeier, Giuseppe Baselli, Mark Jenkinson, Clare E. Mackay, Eugene P. Duff, Ludovica Griffanti
Integrating large-scale neuroimaging research datasets: Harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets. NeuroImage 237 (2021)
Jorge Corral Acero, Vaanathi Sundaresan, Nicola K. Dinsdale, Vicente Grau, Mark Jenkinson
A 2-Step Deep Learning Method with Domain Adaptation for Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Magnetic Resonance Segmentation. M&Ms and EMIDEC/STACOM@MICCAI (2020)
Vaanathi Sundaresan, Ludovica Griffanti, Mark Jenkinson
Brain Tumour Segmentation Using a Triplanar Ensemble of U-Nets on MR Images. BrainLes@MICCAI (1) (2020)
Vaanathi Sundaresan, Ludovica Griffanti, Petya Kindalova, Fidel Alfaro-Almagro, Giovanna Zamboni, Peter M. Rothwell, Thomas E. Nichols, Mark Jenkinson
Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference. NeuroImage 185 (2019)
Vaanathi Sundaresan, Giovanna Zamboni, Campbell Le Heron, Peter M. Rothwell, Masud Husain, Marco Battaglini, Nicola De Stefano, Mark Jenkinson, Ludovica Griffanti
Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding. NeuroImage 202 (2019)
Vaanathi Sundaresan, Christopher P. Bridge, Christos Ioannou, J. Alison Noble
Automated characterization of the fetal heart in ultrasound images using fully convolutional neural networks. ISBI (2017)
Ludovica Griffanti, Giovanna Zamboni, Aamira Khan, Linxin Li, Guendalina Bonifacio, Vaanathi Sundaresan, Ursula G. Schulz, Wilhelm Kuker, Marco Battaglini, Peter M. Rothwell, Mark Jenkinson
BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities. NeuroImage 141 (2016)
Vaanathi Sundaresan, Keerthi Ram, Niranjan Joshi, Mohanasankar Sivaprakasam, Rashmin Gandhi
Computer-assisted grading of diabetic macular edema on retinal color fundus images. EMBC (2015)