Konrad Werys

580 total citations
29 papers, 349 citations indexed

About

Konrad Werys is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Konrad Werys has authored 29 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Cardiology and Cardiovascular Medicine, 23 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Konrad Werys's work include Cardiac Imaging and Diagnostics (16 papers), Advanced MRI Techniques and Applications (16 papers) and Cardiovascular Function and Risk Factors (15 papers). Konrad Werys is often cited by papers focused on Cardiac Imaging and Diagnostics (16 papers), Advanced MRI Techniques and Applications (16 papers) and Cardiovascular Function and Risk Factors (15 papers). Konrad Werys collaborates with scholars based in United Kingdom, Poland and United States. Konrad Werys's co-authors include Łukasz A. Małek, Stefan K. Piechnik, Mateusz Śpiewak, Joanna Petryka, Elena Lukaschuk, Łukasz Mazurkiewicz, Qiang Zhang, Vanessa M. Ferreira, Iulia A. Popescu and Magdalena Marczak and has published in prestigious journals such as PLoS ONE, Radiology and Journal of Magnetic Resonance Imaging.

In The Last Decade

Konrad Werys

29 papers receiving 344 citations

Peers

Konrad Werys
Konrad Werys
Citations per year, relative to Konrad Werys Konrad Werys (= 1×) peers Sigve Karlsen

Countries citing papers authored by Konrad Werys

Since Specialization
Citations

This map shows the geographic impact of Konrad Werys's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Konrad Werys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Konrad Werys more than expected).

Fields of papers citing papers by Konrad Werys

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Konrad Werys. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Konrad Werys. The network helps show where Konrad Werys may publish in the future.

Co-authorship network of co-authors of Konrad Werys

This figure shows the co-authorship network connecting the top 25 collaborators of Konrad Werys. A scholar is included among the top collaborators of Konrad Werys based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Konrad Werys. Konrad Werys is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gaiolla, Rafael Dezen, Konrad Werys, Suzana Érico Tanni, et al.. (2021). Characterization of subclinical diastolic dysfunction by cardiac magnetic resonance feature-tracking in adult survivors of non-Hodgkin lymphoma treated with anthracyclines. BMC Cardiovascular Disorders. 21(1). 170–170. 9 indexed citations
2.
Thompson, Elizabeth, Srikant Kamesh Iyer, Michael Solomon, et al.. (2021). Endogenous T1ρ cardiovascular magnetic resonance in hypertrophic cardiomyopathy. Journal of Cardiovascular Magnetic Resonance. 23(1). 120–120. 27 indexed citations
3.
Gonzales, Ricardo A., Qiang Zhang, Bartłomiej W. Papież, et al.. (2021). MOCOnet: Robust Motion Correction of Cardiovascular Magnetic Resonance T1 Mapping Using Convolutional Neural Networks. Frontiers in Cardiovascular Medicine. 8. 768245–768245. 11 indexed citations
4.
Zhang, Qiang, Konrad Werys, Iulia A. Popescu, et al.. (2020). Deep learning with attention supervision for automated motion artefact detection in quality control of cardiac T1-mapping. Artificial Intelligence in Medicine. 110. 101955–101955. 31 indexed citations
5.
Popescu, Iulia A., Konrad Werys, Qiang Zhang, et al.. (2020). Standardization of T1-mapping in cardiovascular magnetic resonance using clustered structuring for benchmarking normal ranges. International Journal of Cardiology. 326. 220–225. 18 indexed citations
6.
Biasiolli, Luca, Elena Lukaschuk, Valentina Carapella, et al.. (2019). Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data. PLoS ONE. 14(2). e0212272–e0212272. 24 indexed citations
7.
Carapella, Valentina, Elena Lukaschuk, Claudia Marini, et al.. (2019). Standardized image post-processing of cardiovascular magnetic resonance T1-mapping reduces variability and improves accuracy and consistency in myocardial tissue characterization. International Journal of Cardiology. 298. 128–134. 15 indexed citations
8.
Małek, Łukasz A., Anna Czajkowska, Anna Mróz, et al.. (2019). Left ventricular hypertrophy in middle-aged endurance athletes. Blood Pressure Monitoring. 24(3). 110–113. 12 indexed citations
9.
Małek, Łukasz A., Konrad Werys, Anna Czajkowska, et al.. (2019). Cardiovascular magnetic resonance with parametric mapping in long-term ultra-marathon runners. European Journal of Radiology. 117. 89–94. 35 indexed citations
10.
Zhang, Xingyu, Fernanda Bellolio, Pau Medrano−Gracia, et al.. (2019). Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department. BMC Medical Informatics and Decision Making. 19(1). 287–287. 18 indexed citations
11.
Werys, Konrad, Iulius Dragonu, Qiang Zhang, et al.. (2019). Total Mapping Toolbox (TOMATO): An open source library for cardiac magnetic resonance parametric mapping. SoftwareX. 11. 100369–100369. 6 indexed citations
12.
Fung, Kenneth, Luca Biasiolli, Nay Aung, et al.. (2019). 282Reference values for aortic distensibility derived from UK Biobank cardiovascular magnetic resonance (CMR) imaging cohort. European Heart Journal - Cardiovascular Imaging. 20(Supplement_2). 4 indexed citations
14.
Mazurkiewicz, Łukasz, Ewa Orłowska‐Baranowska, Joanna Petryka, et al.. (2017). Systolic myocardial volume gain in dilated, hypertrophied and normal heart. CMR study. Clinical Radiology. 72(4). 286–292. 5 indexed citations
15.
Śpiewak, Mateusz, et al.. (2017). Four-dimensional flow magnetic resonance imaging in hypertrophic obstructive cardiomyopathy. Kardiologia Polska. 75(8). 813–813. 1 indexed citations
16.
Mazurkiewicz, Łukasz, Joanna Petryka, Mateusz Śpiewak, et al.. (2017). Biventricular mechanics in prediction of severe myocardial fibrosis in patients with dilated cardiomyopathy: CMR study. European Journal of Radiology. 91. 71–81. 9 indexed citations
17.
Śpiewak, Mateusz, Mariusz Kłopotowski, Ewa Kowalik, et al.. (2016). Quantification of mitral regurgitation in patients with hypertrophic cardiomyopathy using aortic and pulmonary flow data: impacts of left ventricular outflow tract obstruction and different left ventricular segmentation methods. Journal of Cardiovascular Magnetic Resonance. 19(1). 105–105. 9 indexed citations
18.
Małek, Łukasz A., Konrad Werys, Mariusz Kłopotowski, et al.. (2015). Native T1-mapping for non-contrast assessment of myocardial fibrosis in patients with hypertrophic cardiomyopathy — comparison with late enhancement quantification. Magnetic Resonance Imaging. 33(6). 718–724. 31 indexed citations
19.
Śpiewak, Mateusz, Łukasz A. Małek, Joanna Petryka, et al.. (2012). Repaired Tetralogy of Fallot: Ratio of Right Ventricular Volume to Left Ventricular Volume as a Marker of Right Ventricular Dilatation. Radiology. 265(1). 78–86. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Rankless by CCL
2026