48 citations · 117 across the 9 of their papers we have counts for
16 papers
Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation
Esther Puyol-Anton, Bram Ruijsink, Stefan K. Piechnik +4
The subject of "fairness" in artificial intelligence (AI) refers to assessing AI algorithms for potential bias based on demographic characteristics such as race and gender, and the…
A radiomics approach to analyze cardiac alterations in hypertension
Irem Cetin, Steffen E. Petersen, Sandy Napel +3
Hypertension is a medical condition that is well-established as a risk factor for many major diseases. For example, it can cause alterations in the cardiac structure and function o…
Fully Automated Myocardial Strain Estimation from CMR Tagged Images using a Deep Learning Framework in the UK Biobank
Edward Ferdian, Avan Suinesiaputra, Kenneth Fung +9
Purpose: To demonstrate the feasibility and performance of a fully automated deep learning framework to estimate myocardial strain from short-axis cardiac magnetic resonance tagged…
A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
Irem Cetin, Gerard Sanroma, Steffen E. Petersen +4
Use expert visualization or conventional clinical indices can lack accuracy for borderline classications. Advanced statistical approaches based on eigen-decomposition have been mos…
Combining Multi-Sequence and Synthetic Images for Improved Segmentation of Late Gadolinium Enhancement Cardiac MRI
Víctor M. Campello, Carlos Martín-Isla, Cristian Izquierdo +3
Accurate segmentation of the cardiac boundaries in late gadolinium enhancement magnetic resonance images (LGE-MRI) is a fundamental step for accurate quantification of scar tissue.…
Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image
Chen Qin, Wenjia Bai, Jo Schlemper +4
Accelerating the acquisition of magnetic resonance imaging (MRI) is a challenging problem, and many works have been proposed to reconstruct images from undersampled k-space data. H…