Search Results for author: Rohan Dharmakumar

Found 7 papers, 5 papers with code

The MRI Scanner as a Diagnostic: Image-less Active Sampling

no code implementations24 Jun 2024 Yuning Du, Rohan Dharmakumar, Sotirios A. Tsaftaris

Despite the high diagnostic accuracy of Magnetic Resonance Imaging (MRI), using MRI as a Point-of-Care (POC) disease identification tool poses significant accessibility challenges due to the use of high magnetic field strength and lengthy acquisition times.

Image Reconstruction

Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction

1 code implementation25 Sep 2023 Yuning Du, Yuyang Xue, Rohan Dharmakumar, Sotirios A. Tsaftaris

Deep learning (DL) reconstruction particularly of MRI has led to improvements in image fidelity and reduction of acquisition time.

Fairness MRI Reconstruction

Semi-supervised Pathology Segmentation with Disentangled Representations

1 code implementation5 Sep 2020 Haochuan Jiang, Agisilaos Chartsias, Xinheng Zhang, Giorgos Papanastasiou, Scott Semple, Mark Dweck, David Semple, Rohan Dharmakumar, Sotirios A. Tsaftaris

The model is trained in a semi-supervised fashion with new reconstruction losses directly aiming to improve pathology segmentation with limited annotations.

Anatomy Disentanglement +1

Disentangled Representation Learning in Cardiac Image Analysis

4 code implementations22 Mar 2019 Agisilaos Chartsias, Thomas Joyce, Giorgos Papanastasiou, Michelle Williams, David Newby, Rohan Dharmakumar, Sotirios A. Tsaftaris

We can venture further and consider that a medical image naturally factors into some spatial factors depicting anatomy and factors that denote the imaging characteristics.

Anatomy Computed Tomography (CT) +3

Factorised spatial representation learning: application in semi-supervised myocardial segmentation

1 code implementation19 Mar 2018 Agisilaos Chartsias, Thomas Joyce, Giorgos Papanastasiou, Scott Semple, Michelle Williams, David Newby, Rohan Dharmakumar, Sotirios A. Tsaftaris

Specifically, we achieve comparable performance to fully supervised networks using a fraction of labelled images in experiments on ACDC and a dataset from Edinburgh Imaging Facility QMRI.

Medical Image Segmentation Myocardium Segmentation +1

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