Ivana Išgum
About
Ivana Išgum is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Pulmonary and Respiratory Medicine.
According to data from OpenAlex, Ivana Išgum has authored 196 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 127 papers in Radiology, Nuclear Medicine and Imaging, 67 papers in Biomedical Engineering and 44 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ivana Išgum's work include Cardiac Imaging and Diagnostics (90 papers), Advanced X-ray and CT Imaging (63 papers) and Medical Imaging Techniques and Applications (48 papers). Ivana Išgum is often cited by papers focused on Cardiac Imaging and Diagnostics (90 papers), Advanced X-ray and CT Imaging (63 papers) and Medical Imaging Techniques and Applications (48 papers). Ivana Išgum collaborates with scholars based in Netherlands, United States and Germany. Ivana Išgum's co-authors include Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, Bram van Ginneken, Bob D. de Vos, Pim A. de Jong, Mathias Prokop, Nikolas Leßmann, Marius Staring and Manon J.N.L. Benders and has published in prestigious journals such as JAMA, PLoS ONE and NeuroImage.
In The Last Decade
Ivana Išgum
190 papers receiving 7.4k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Ivana Išgum Netherlands | 48 | 4.4k | 2.5k | 1.6k | 1.3k | 1.2k | 196 | 7.5k | ||
| Sandy Napel United States | 57 | 5.9k 1.3× | 1.9k 0.7× | 3.6k 2.2× | 1.6k 1.2× | 453 0.4× | 190 | 9.8k | ||
| Stefan Klein Netherlands | 39 | 4.5k 1.0× | 1.9k 0.7× | 1.3k 0.8× | 2.5k 1.9× | 652 0.5× | 253 | 9.0k | ||
| Ben Glocker United Kingdom | 40 | 3.4k 0.8× | 1.5k 0.6× | 572 0.4× | 5.0k 3.7× | 262 0.2× | 151 | 10.1k | ||
| Reza Razavi United Kingdom | 51 | 4.6k 1.1× | 1.8k 0.7× | 1.6k 1.0× | 571 0.4× | 6.2k 5.2× | 447 | 10.8k | ||
| Marius Staring Netherlands | 28 | 3.4k 0.8× | 1.5k 0.6× | 967 0.6× | 2.6k 1.9× | 300 0.3× | 109 | 6.7k | ||
| Massimo Mischi Netherlands | 38 | 1.7k 0.4× | 2.4k 0.9× | 1.4k 0.8× | 212 0.2× | 1.1k 0.9× | 368 | 5.2k | ||
| Dong Ni China | 43 | 2.2k 0.5× | 854 0.3× | 653 0.4× | 1.8k 1.4× | 141 0.1× | 232 | 6.8k | ||
| Kyongtae T. Bae United States | 57 | 4.2k 1.0× | 2.0k 0.8× | 2.2k 1.3× | 277 0.2× | 483 0.4× | 192 | 10.5k | ||
| Luca Saba Italy | 50 | 3.8k 0.9× | 1.2k 0.5× | 5.0k 3.1× | 594 0.4× | 3.9k 3.2× | 580 | 11.8k | ||
| Julia A. Schnabel United Kingdom | 31 | 2.6k 0.6× | 1.0k 0.4× | 428 0.3× | 2.1k 1.6× | 253 0.2× | 188 | 4.8k |
Countries citing papers authored by Ivana Išgum
Since
Specialization
Citations
This map shows the geographic impact of Ivana Išgum'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 Ivana Išgum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivana Išgum more than expected).
Fields of papers citing papers by Ivana Išgum
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Ivana Išgum. 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 Ivana Išgum. The network helps show where Ivana Išgum may publish in the future.
Co-authorship network of co-authors of Ivana Išgum
This figure shows the co-authorship network connecting the top 25 collaborators of Ivana Išgum. A scholar is included among the top collaborators of Ivana Išgum 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 Ivana Išgum. Ivana Išgum is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Mol, Jan‐Quinten, Mathias Prokop, Bram van Ginneken, et al.. (2025). Comprehensive full-vessel segmentation and volumetric plaque quantification for intracoronary optical coherence tomography using deep learning. European Heart Journal - Digital Health. 6(3). 404–416.
2.
Meulendijks, Eva R., Etto C. Eringa, Ron A. Hoebe, et al.. (2025). Patients with persistent atrial fibrillation and metabolic comorbidities have an altered inflammatory state of atrial epicardial adipose tissue, which is linked to CT-attenuation. Cardiovascular Diabetology. 25(1).
3.
Mavroveli, Stella, Martin Wagner, Ivana Išgum, et al.. (2025). Assessment of the extent of lymphadenectomy in esophageal cancer surgery in the observational tiger study: [TIGER-SQA] study protocol. Pure Amsterdam UMC. 5(1). 36–45.
4.
Xu, Kaiwen, Ho Hin Lee, Shunxing Bao, et al.. (2024). Inter-vendor harmonization of CT reconstruction kernels using unpaired image translation. PubMed. 12926. 45–45.
5.
Velzen, Sanne G. M. van, et al.. (2024). Deep learning-based prediction of fractional flow reserve after invasive coronary artery treatment. Pure Amsterdam UMC. 11596. 12–12.
6.
Vos, Bob D. de, et al.. (2024). Automated echocardiography view classification and quality assessment with recognition of unknown views. Journal of Medical Imaging. 11(5). 54002–54002.
7.
Bouma, Berto J., Ivana Išgum, Niels Verouden, et al.. (2023). The impact of valvular heart disease in patients with chronic coronary syndrome. Frontiers in Cardiovascular Medicine. 10. 1211322–1211322.
8.
Kosińska–Kaczyńska, Katarzyna, et al.. (2023). Deep learning for estimation of fetal weight throughout the pregnancy from fetal abdominal ultrasound. American Journal of Obstetrics & Gynecology MFM. 5(12). 101182–101182.
9.
Brawura-Biskupski-Samaha, Robert, Paweł Gutaj, Michał Lipa, et al.. (2023). BabyNet＋＋: Fetal birth weight prediction using biometry multimodal data acquired less than 24 hours before delivery. Computers in Biology and Medicine. 167. 107602–107602.
10.
Bruggeman, Agnetha A.E., Ivana Išgum, Efstratios Gavves, et al.. (2022). Deep-Learning-Based Thrombus Localization and Segmentation in Patients with Posterior Circulation Stroke. Diagnostics. 12(6). 1400–1400.
11.
Pundziūtė, Gabija, Carlijn M. van der Aalst, Jan W. Gratama, et al.. (2022). Early detection of obstructive coronary artery disease in the asymptomatic high-risk population: objectives and study design of the EARLY-SYNERGY trial. American Heart Journal. 246. 166–177.
12.
Lin, Andrew, Márton Kolossváry, Manish Motwani, et al.. (2021). Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease. Radiology Cardiothoracic Imaging. 3(1). e200512–e200512.
13.
Emaus, Marleen J., Ivana Išgum, Sanne G. M. van Velzen, et al.. (2019). Bragatston study protocol: a multicentre cohort study on automated quantification of cardiovascular calcifications on radiotherapy planning CT scans for cardiovascular risk prediction in patients with breast cancer. BMJ Open. 9(7). e028752–e028752.
14.
Wolterink, Jelmer M., Robbert W. van Hamersvelt, Max A. Viergever, Tim Leiner, & Ivana Išgum. (2018). Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier. Medical Image Analysis. 51. 46–60.
15.
Harder, Annemarie M. den, Pim A. de Jong, Mark de Groot, et al.. (2018). Commonly available hematological biomarkers are associated with the extent of coronary calcifications. Atherosclerosis. 275. 166–173.
16.
Zreik, Majd, Robbert W. van Hamersvelt, Jelmer M. Wolterink, et al.. (2018). Automatic Detection and Characterization of Coronary Artery Plaque and Stenosis using a Recurrent Convolutional Neural Network in Coronary CT Angiography. arXiv (Cornell University).
17.
Willemink, Martin J., Richard A. P. Takx, Ivana Išgum, et al.. (2015). Prognostic value of heart valve calcifications for cardiovascular events in a lung cancer screening population. International journal of cardiac imaging. 31(6). 1243–1249.
18.
Takx, Richard A. P., Rozemarijn Vliegenthart, Firdaus A. A. Mohamed Hoesein, et al.. (2014). Pulmonary function and CT biomarkers as risk factors for cardiovascular events in male lung cancer screening participants: the NELSON study. European Radiology. 25(1). 65–71.
19.
Mets, Onno M., Michael A. Schmidt, Constantinus F. M. Buckens, et al.. (2013). Diagnosis of chronic obstructive pulmonary disease in lung cancer screening Computed Tomography scans: independent contribution of emphysema, air trapping and bronchial wall thickening. Respiratory Research. 14(1). 59–59.
20.
Setten, Jessica van, Ivana Išgum, Joanna Smolonska, et al.. (2013). Genome-wide association study of coronary and aortic calcification implicates risk loci for coronary artery disease and myocardial infarction. Atherosclerosis. 228(2). 400–405.
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.
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