Dr Rashed Karim received his BSc from the University of Toronto and his MSc with Distinction from Queen Mary, University of London. He obtained a PhD in medical image analysis from the Department of Computing at Imperial College London. He is an Honorary Lecturer at Imperial College London.
He currently specialises in software for knowledge discovery from high resolution medical imaging data (CT, MRI, X-Ray) using cutting-edge algorithms from computer vision, image processing and visualisation.
His major works include visualising atrial fibrosis in MRI datasets, algorithm evaluation for left atrial wall thickness and measuring myocardial infarction. He has also proposed methods for creating 2D maps of the heart from CMR images.
et al., The Effect of Contact Force in Atrial Radiofrequency Ablation : Electroanatomical, Cardiovascular Magnetic Resonance, and Histological Assessment in a Chronic Porcine Model, Jacc: Clinical Electrophysiology
et al., 2016, Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images, Medical Image Analysis, Vol:30, ISSN:1361-8415, Pages:95-107
et al., 2016, Three-Degree-of-Freedom MR-Compatible Multisegment Cardiac Catheter Steering Mechanism, Ieee Transactions on Biomedical Engineering, Vol:63, ISSN:0018-9294, Pages:2425-2435
et al., 2015, A randomized prospective mechanistic cardiac magnetic resonance study correlating catheter stability, late gadolinium enhancement and 3 year clinical outcomes in robotically assisted vs. standard catheter ablation., Europace, Vol:17, Pages:1241-1250
et al., 2015, Response to letter from Bisbal et al regarding, "Repeat left atrial catheter ablation: cardiac magnetic resonance prediction of endocardial voltage and gaps in ablation lesion sets"., Circ Arrhythm Electrophysiol, Vol:8, Pages:754-755