1 code implementation • 19 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.
4 code implementations • 22 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.
2 code implementations • 11 Nov 2019 • Agisilaos Chartsias, Giorgos Papanastasiou, Chengjia Wang, Scott Semple, David E. Newby, Rohan Dharmakumar, Sotirios A. Tsaftaris
Core to our method is learning a disentangled decomposition into anatomical and imaging factors.
1 code implementation • 5 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.
no code implementations • 25 Aug 2023 • Dilek M. Yalcinkaya, Khalid Youssef, Bobak Heydari, Orlando Simonetti, Rohan Dharmakumar, Subha Raman, Behzad Sharif
In the proposed approach, we referred the top 10% most uncertain segmentations as detected by our dQC tool to the human expert for refinement.
1 code implementation • 25 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.