5 citations · 8 across the 4 of their papers we have counts for
4 papers
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge
Kang Wang, Chen Qin, Zhang Shi +46
Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…
Explainable Image Quality Assessment for Medical Imaging
Caner Ozer, Arda Guler, Aysel Turkvatan Cansever +1
Medical image quality assessment is an important aspect of image acquisition, as poor-quality images may lead to misdiagnosis. Manual labelling of image quality is a tedious task f…
Detecting respiratory motion artefacts for cardiovascular MRIs to ensure high-quality segmentation
Amin Ranem, John Kalkhof, Caner Özer +2
While machine learning approaches perform well on their training domain, they generally tend to fail in a real-world application. In cardiovascular magnetic resonance imaging (CMR)…
Shifted Windows Transformers for Medical Image Quality Assessment
Caner Ozer, Arda Guler, Aysel Turkvatan Cansever +3
To maintain a standard in a medical imaging study, images should have necessary image quality for potential diagnostic use. Although CNN-based approaches are used to assess the ima…