Phone: +31 88 75 50565
LinkedIn; Google Scholar
In 2008 Majd obtained his Bachelor of Science degree in Biomedical Engineering at the Technion – Israel Institute of Technology, Haifa, Israel. In 2010 he received his Master’s Degree also in Biomedical Engineering at Tel Aviv University. His master’s thesis focused on signal processing techniques on in-vivo brain signals. From 2010 until 2015 he worked as algorithms engineer/team leader in the biomedical industry. In 2015 he started as a PhD-candidate at the Image Sciences Institute at UMC Utrecht where his main area of research is assessment of cardiovascular risk from Coronary CT Angiography (CCTA). Majd is interested in image processing, quantitative imaging and machine learning.
|1.||Deep learning-based analysis of the left ventricular myocardium in coronary CTA images improves specificity for detection of functionally significant coronary artery stenosis. European Congress of Radiology (ECR), 2018
|2.||Improving Specificity of Coronary CT Angiography for the Detection of Functionally Significant Coronary Artery Disease: A Deep Learning Approach. Radiological Society of North America, 103rd Annual Meeting , 2017
|3.||Deep learning analysis of the left ventricular myocardium in cardiac CT images enables detection of functionally significant coronary artery stenosis regardless of coronary anatomy. Radiological Society of North America, 103rd Annual Meeting , 2017