activity
20172022
most citedSelf-Supervised Learning for Spinal MRIs

15 citations · 26 across the 4 of their papers we have counts for

collaborators

5 papers

eess.IV20227 cited

SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans

Rhydian Windsor, Amir Jamaludin, Timor Kadir +1

This technical report presents SpineNetV2, an automated tool which: (i) detects and labels vertebral bodies in clinical spinal magnetic resonance (MR) scans across a range of commo…

cs.CV2021

Self-Supervised Multi-Modal Alignment for Whole Body Medical Imaging

Rhydian Windsor, Amir Jamaludin, Timor Kadir +1

This paper explores the use of self-supervised deep learning in medical imaging in cases where two scan modalities are available for the same subject. Specifically, we use a large…

cs.LG20214 cited

A Deep Learning Approach to Private Data Sharing of Medical Images Using Conditional GANs

Hanxi Sun, Jason Plawinski, Sajanth Subramaniam +7

Sharing data from clinical studies can facilitate innovative data-driven research and ultimately lead to better public health. However, sharing biomedical data can put sensitive pe…

eess.IV2020

A Convolutional Approach to Vertebrae Detection and Labelling in Whole Spine MRI

Rhydian Windsor, Amir Jamaludin, Timor Kadir +1

We propose a novel convolutional method for the detection and identification of vertebrae in whole spine MRIs. This involves using a learnt vector field to group detected vertebrae…

cs.CV201715 cited

Self-Supervised Learning for Spinal MRIs

Amir Jamaludin, Timor Kadir, Andrew Zisserman

A significant proportion of patients scanned in a clinical setting have follow-up scans. We show in this work that such longitudinal scans alone can be used as a form of 'free' sel…