Ioannis Sechopoulos

7.1k total citations · 2 hit papers
198 papers, 4.8k citations indexed

About

Ioannis Sechopoulos is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Ioannis Sechopoulos has authored 198 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 160 papers in Radiology, Nuclear Medicine and Imaging, 124 papers in Pulmonary and Respiratory Medicine and 78 papers in Biomedical Engineering. Recurrent topics in Ioannis Sechopoulos's work include Digital Radiography and Breast Imaging (119 papers), Medical Imaging Techniques and Applications (104 papers) and Advanced X-ray and CT Imaging (72 papers). Ioannis Sechopoulos is often cited by papers focused on Digital Radiography and Breast Imaging (119 papers), Medical Imaging Techniques and Applications (104 papers) and Advanced X-ray and CT Imaging (72 papers). Ioannis Sechopoulos collaborates with scholars based in Netherlands, United States and Italy. Ioannis Sechopoulos's co-authors include Ritse M. Mann, Alejandro Rodríguez‐Ruiz, Carl J. D’Orsi, Steve Si Jia Feng, Jonas Teuwen, Andrew Karellas, Sankararaman Suryanarayanan, Srinivasan Vedantham, Marco Caballo and Sylvia H. Heywang‐Köbrunner and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biomaterials.

In The Last Decade

Ioannis Sechopoulos

180 papers receiving 4.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists

2018 405 citations Alejandro Rodríguez‐Ruiz, Mireille J. M. Broeders et al. profile →
Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System

2018 401 citations Alejandro Rodríguez‐Ruiz, Ioannis Sechopoulos et al. Radiology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ioannis Sechopoulos Netherlands	33	3.6k	2.7k	2.0k	1.5k	459	198	4.8k
Isaac Shiri Switzerland	36	2.9k 0.8×	860 0.3×	544 0.3×	1.4k 0.9×	200 0.4×	174	3.6k
Binsheng Zhao United States	46	4.3k 1.2×	3.1k 1.2×	796 0.4×	1.3k 0.9×	1.3k 2.8×	140	6.5k
Andrew D. A. Maidment United States	38	2.7k 0.8×	2.7k 1.0×	1.4k 0.7×	1.5k 1.0×	316 0.7×	272	4.4k
Katja Pinker Austria	56	6.5k 1.8×	1.3k 0.5×	1.3k 0.7×	739 0.5×	775 1.7×	282	8.7k
Henkjan Huisman Netherlands	41	4.4k 1.2×	4.6k 1.7×	785 0.4×	693 0.5×	223 0.5×	124	6.5k
Emmanuel Rios Velazquez United States	20	6.6k 1.8×	3.0k 1.1×	1.3k 0.6×	1.9k 1.3×	1.3k 2.7×	32	7.4k
Stephanie Tanadini‐Lang Switzerland	36	3.0k 0.8×	2.1k 0.8×	317 0.2×	812 0.5×	599 1.3×	163	4.7k
Aniek J.G. Even Netherlands	14	3.7k 1.0×	1.5k 0.6×	506 0.3×	962 0.6×	806 1.8×	21	4.3k
Rivka R. Colen United States	34	2.1k 0.6×	915 0.3×	653 0.3×	489 0.3×	535 1.2×	138	4.2k
Arthur Jochems Netherlands	24	4.4k 1.2×	1.8k 0.7×	877 0.4×	1.2k 0.8×	1.1k 2.3×	42	5.5k

Countries citing papers authored by Ioannis Sechopoulos

Since Specialization

Citations

This map shows the geographic impact of Ioannis Sechopoulos'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 Ioannis Sechopoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ioannis Sechopoulos more than expected).

Fields of papers citing papers by Ioannis Sechopoulos

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ioannis Sechopoulos. 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 Ioannis Sechopoulos. The network helps show where Ioannis Sechopoulos may publish in the future.

Co-authorship network of co-authors of Ioannis Sechopoulos

This figure shows the co-authorship network connecting the top 25 collaborators of Ioannis Sechopoulos. A scholar is included among the top collaborators of Ioannis Sechopoulos 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 Ioannis Sechopoulos. Ioannis Sechopoulos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Sechopoulos, Ioannis, et al.. (2026). Finding the optimal recall rate in breast cancer screening: results from the ROCS study. European Radiology.

Frush, Donald P., Armin Ansari, James A. Brink, et al.. (2025). Expert panel on monitoring radiation doses from recurrent medical diagnostic procedures: Sixth Gilbert W. Beebe Webinar. Journal of Applied Clinical Medical Physics. 26(4). e70022–e70022. 1 indexed citations

Schiaffino, Simone, Daniela Bernardi, Nuala Healy, et al.. (2025). ESR Essentials: artificial intelligence in breast imaging—practice recommendations by the European Society of Breast Imaging. European Radiology. 36(3). 1909–1918. 1 indexed citations

Sechopoulos, Ioannis, Alejandro Rodríguez‐Ruiz, Wouter J. H. Veldkamp, et al.. (2025). An Exploration of Discrepant Recalls Between AI and Human Readers of Malignant Lesions in Digital Mammography Screening. Diagnostics. 15(12). 1566–1566.

Kroes, J.G., Elizabeth Loehrer, Ioannis Sechopoulos, et al.. (2025). AI as an independent second reader in detection of clinically relevant breast cancers within a population-based screening programme in the Netherlands: a retrospective cohort study. The Lancet Digital Health. 7(8). 100882–100882. 1 indexed citations

Smit, Ewoud J., et al.. (2024). Performance evaluation of a 4D similarity filter for dynamic CT angiography imaging of the liver. Medical Physics. 51(12). 8814–8827. 1 indexed citations

Oostveen, Luuk J., et al.. (2024). Perceptual thresholds for differences in CT noise texture. Journal of Medical Imaging. 11(3). 35501–35501.

Michielsen, Koen, et al.. (2024). Technical note: Characterization, validation, and spectral optimization of a dedicated breast CT system for contrast‐enhanced imaging. Medical Physics. 51(5). 3322–3333. 2 indexed citations

Michielsen, Koen, et al.. (2024). CASYMIR: a generalized cascaded linear system model implementation for x-ray detectors. University of Twente Research Information. 13–13. 1 indexed citations

10.

Hummelink, Stefan, et al.. (2024). Automatic analysis of the scapholunate distance using 4DCT imaging: normal values in the healthy wrist. Clinical Radiology. 79(8). e1040–e1048. 5 indexed citations

11.

Michielsen, Koen, et al.. (2023). A deep learning approach to estimate x‐ray scatter in digital breast tomosynthesis: From phantom models to clinical applications. Medical Physics. 50(8). 4744–4757. 2 indexed citations

12.

Rodríguez‐Ruiz, Alejandro, Mehmet Ufuk Dalmış, Nico Karssemeijer, et al.. (2022). Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms. Radiology. 303(2). 269–275. 37 indexed citations

13.

Rodríguez‐Ruiz, Alejandro, et al.. (2021). Impact of Artificial Intelligence Decision Support Using Deep Learning on Breast Cancer Screening Interpretation with Single-View Wide-Angle Digital Breast Tomosynthesis. Radiology. 300(3). 529–536. 54 indexed citations

14.

Hansen, Hendrik H.G., Bogdan Maris, Vincent Groenhuis, et al.. (2019). Ultrasound-guided breast biopsy of ultrasound occult lesions using multimodality image co-registration and tissue displacement tracking. University of Twente Research Information. 1 indexed citations

15.

Grob, D., Ewoud J. Smit, Jip F. Prince, et al.. (2019). Iodine Maps from Subtraction CT or Dual-Energy CT to Detect Pulmonary Emboli with CT Angiography: A Multiple-Observer Study. Radiology. 292(1). 197–205. 38 indexed citations

16.

Brombal, Luca, F. Arfelli, P. Delogu, et al.. (2019). Image quality comparison between a phase-contrast synchrotron radiation breast CT and a clinical breast CT: a phantom based study. Scientific Reports. 9(1). 17778–17778. 24 indexed citations

17.

Fedon, Christian, Marco Caballo, Oliver Díaz, et al.. (2018). Monte Carlo study on optimal breast voxel resolution for dosimetry estimates in digital breast tomosynthesis. Physics in Medicine and Biology. 64(1). 15003–15003. 6 indexed citations

18.

Caballo, Marco, Christian Fedon, Luca Brombal, et al.. (2018). Development of 3D patient-based super-resolution digital breast phantoms using machine learning. Physics in Medicine and Biology. 63(22). 225017–225017. 12 indexed citations

19.

Sechopoulos, Ioannis, Andreu Badal, Aldo Badano, et al.. (2011). WE‐G‐110‐06: Introduction to the AAPM Task Group No. 195 ‐ Monte Carlo Reference Data Sets for Imaging Research. Medical Physics. 38(6Part33). 3834–3834. 1 indexed citations

20.

Sechopoulos, Ioannis, Sankararaman Suryanarayanan, Srinivasan Vedantham, Carl J. D’Orsi, & Andrew Karellas. (2006). Computation of the glandular radiation dose in digital tomosynthesis of the breast. Medical Physics. 34(1). 221–232. 113 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.

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