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20202026
most citedSpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans

7 citations · 15 across the 8 of their papers we have counts for

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5 papers · 1 filter

eess.IV2026

Rendering Novel Views of MRI Using 3D Gaussian Splatting

Robin Y. Park, Mark C. Eid, Rhydian Windsor +4

The objective of this paper is to improve radiological gradings measured on MRIs of spines, by resampling scans so that the new view planes are better aligned with the target anato…

eess.IV2024★ 3 cited

Automated Spinal MRI Labelling from Reports Using a Large Language Model

Robin Y. Park, Rhydian Windsor, Amir Jamaludin +1

We propose a general pipeline to automate the extraction of labels from radiology reports using large language models, which we validate on spinal MRI reports. The efficacy of our…

eess.IV2022★ 1 cited

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…

eess.IV2022★ 7 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…

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…