15 citations · 31 across the 8 of their papers we have counts for
9 papers
Predicting Spine Geometry and Scoliosis from DXA Scans
Amir Jamaludin, Timor Kadir, Emma Clark +1
Our objective in this paper is to estimate spine curvature in DXA scans. To this end we first train a neural network to predict the middle spine curve in the scan, and then use an…
Contouring by Unit Vector Field Regression
Amir Jamaludin, Sarim Ather, Timor Kadir +1
This work introduces a simple deep-learning based method to delineate contours by `walking' along learnt unit vector fields. We demonstrate the effectiveness of our pipeline on the…
Vision-Language Modelling For Radiological Imaging and Reports In The Low Data Regime
Rhydian Windsor, Amir Jamaludin, Timor Kadir +1
This paper explores training medical vision-language models (VLMs) -- where the visual and language inputs are embedded into a common space -- with a particular focus on scenarios…
Context-Aware Transformers For Spinal Cancer Detection and Radiological Grading
Rhydian Windsor, Amir Jamaludin, Timor Kadir +1
This paper proposes a novel transformer-based model architecture for medical imaging problems involving analysis of vertebrae. It considers two applications of such models in MR im…
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…
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…
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…
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…
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…