Stefan K Piechnik
DSc, PhD, MScEE, FSCMR
Associate Professor of Biomedical Imaging
- Head of Advanced Cardiovascular Image Processing
Over the past 30+ years, I have applied my engineering background to interdisciplinary biomedical research, including mathematical and biophysical modelling, measurement systems and methods design, direct clinical measurements, imaging and estimation using PET, SPECT, and MR, and the clinical and self-assessment approaches. Applications include wide range of clinical specialties in Neurosciences (Neurosurgery, Neurology and Psychiatry), Dermatology, Cardiovascular and Internal Medicine. Over the course of my work I co-authored 7 patent applications, >340 research articles, attracting >13'000 citations, resulting in a h-index of 58 . My most recent focus is in the clinical application of CMR parametric tissue characterisation techniques, in particular T1 mapping, big data and the related applications of artificial intelligence.
Towards Replacing Late Gadolinium Enhancement with Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.
Zhang Q. et al, (2021), Circulation
Cardiac stress T1-mapping response and extracellular volume stability of MOLLI-based T1-mapping methods.
Burrage MK. et al, (2021), Sci Rep, 11
Subclinical Changes in Cardiac Functional Parameters as Determined by Cardiovascular Magnetic Resonance (CMR) Imaging in Sleep Apnea and Snoring: Findings from UK Biobank.
Curta A. et al, (2021), Medicina (Kaunas), 57
Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping.
Hann E. et al, (2021), Med Image Anal, 71
Adverse cardiovascular magnetic resonance phenotypes are associated with greater likelihood of incident coronavirus disease 2019: findings from the UK Biobank.
Raisi-Estabragh Z. et al, (2021), Aging Clin Exp Res