Miguel A. Lago

439 total citations
39 papers, 271 citations indexed

About

Miguel A. Lago is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Miguel A. Lago has authored 39 papers receiving a total of 271 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Radiology, Nuclear Medicine and Imaging, 19 papers in Pulmonary and Respiratory Medicine and 13 papers in Artificial Intelligence. Recurrent topics in Miguel A. Lago's work include Digital Radiography and Breast Imaging (18 papers), AI in cancer detection (11 papers) and Medical Imaging Techniques and Applications (10 papers). Miguel A. Lago is often cited by papers focused on Digital Radiography and Breast Imaging (18 papers), AI in cancer detection (11 papers) and Medical Imaging Techniques and Applications (10 papers). Miguel A. Lago collaborates with scholars based in United States, Spain and Belgium. Miguel A. Lago's co-authors include Miguel P. Eckstein, C. Monserrat, María José Rupérez, Craig K. Abbey, Francisco Martínez‐Martínez, Cristina Peris‐Martínez, Predrag R. Bakić, José D. Martín‐Guerrero, Andrew D. A. Maidment and Bruno Barufaldi and has published in prestigious journals such as Current Biology, Optics Express and Expert Systems with Applications.

In The Last Decade

Miguel A. Lago

32 papers receiving 266 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Miguel A. Lago United States 10 160 84 67 56 43 39 271
Tom Kimpe Belgium 9 111 0.7× 53 0.6× 91 1.4× 81 1.4× 79 1.8× 61 309
Juan Morales‐Sánchez Spain 10 188 1.2× 55 0.7× 88 1.3× 177 3.2× 29 0.7× 49 381
N Hangiandreou United States 2 163 1.0× 80 1.0× 140 2.1× 38 0.7× 51 1.2× 3 298
Robert Uzenoff Japan 3 182 1.1× 97 1.2× 151 2.3× 42 0.8× 54 1.3× 4 323
Zhen Tang China 10 64 0.4× 163 1.9× 33 0.5× 60 1.1× 30 0.7× 15 418
Saowapak S. Thongvigitmanee Thailand 8 214 1.3× 220 2.6× 40 0.6× 67 1.2× 25 0.6× 33 492
Maheza Irna Mohamad Salim Malaysia 12 107 0.7× 102 1.2× 20 0.3× 60 1.1× 59 1.4× 37 327
Amir Alansary United States 9 119 0.7× 59 0.7× 18 0.3× 121 2.2× 80 1.9× 17 319
María Helguera United States 10 125 0.8× 121 1.4× 30 0.4× 57 1.0× 16 0.4× 38 316
John Whitaker United Kingdom 21 292 1.8× 92 1.1× 65 1.0× 22 0.4× 13 0.3× 99 1.4k

Countries citing papers authored by Miguel A. Lago

Since Specialization
Citations

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

Fields of papers citing papers by Miguel A. Lago

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miguel A. Lago. 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 Miguel A. Lago. The network helps show where Miguel A. Lago may publish in the future.

Co-authorship network of co-authors of Miguel A. Lago

This figure shows the co-authorship network connecting the top 25 collaborators of Miguel A. Lago. A scholar is included among the top collaborators of Miguel A. Lago 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 Miguel A. Lago. Miguel A. Lago 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.
2.
Barufaldi, Bruno, Miguel A. Lago, Ehsan Abadi, & Andrew D. A. Maidment. (2025). Container applications for the development and integration of virtual imaging platforms. Medical Physics. 52(6). 3685–3696. 1 indexed citations
3.
Beams, Ryan, et al.. (2024). Open-Source Pattern Creation Tool for Medical ExtendedReality Image Quality Assessment. The Journal of Open Source Software. 9(93). 6021–6021. 2 indexed citations
4.
Lago, Miguel A., et al.. (2024). Evaluation of monocular and binocular contrast perception on virtual reality head-mounted displays. Journal of Medical Imaging. 11(6). 62605–62605.
5.
Sizikova, Elena, Andreu Badal, Jana G. Delfino, et al.. (2024). Synthetic data in radiological imaging: current state and future outlook. 1(1). 5 indexed citations
6.
Zhao, Chumin, et al.. (2024). Integrating eye rotation and contrast sensitivity into image quality evaluation of virtual reality head-mounted displays. Optics Express. 32(14). 24968–24968. 1 indexed citations
7.
Levine, Gary M., Weijie Chen, Berkman Sahiner, et al.. (2024). Applying queueing theory to evaluate wait-time-savings of triage algorithms. Queueing Systems. 108(3-4). 579–610. 2 indexed citations
8.
Lago, Miguel A. & Aldo Badano. (2023). Adaptive Laguerre-Gauss channels for detection and search of irregularly shaped lesions. 29–29. 1 indexed citations
9.
Adamo, Stephen H., Bruno Barufaldi, & Miguel A. Lago. (2023). Comparing experts to novices: reduced satisfaction of search when searching with virtual breast tomosynthesis. 72. 1–1.
10.
Adamo, Stephen H., Nelson Roque, Bruno Barufaldi, et al.. (2023). Assessing satisfaction of search in virtual mammograms for experienced and novice searchers. Journal of Medical Imaging. 10(S1).
11.
Lago, Miguel A., et al.. (2023). A 2D Synthesized Image Improves the 3D Search for Foveated Visual Systems. IEEE Transactions on Medical Imaging. 42(8). 2176–2188.
12.
Lago, Miguel A., et al.. (2021). The perceptual influence of 2D synthesized images on 3D search. 16–16. 1 indexed citations
13.
Lago, Miguel A., Craig K. Abbey, Bruno Barufaldi, et al.. (2021). Under-exploration of Three-Dimensional Images Leads to Search Errors for Small Salient Targets. Current Biology. 31(5). 1099–1106.e5. 9 indexed citations
14.
Lago, Miguel A., Ioannis Sechopoulos, François Bochud, & Miguel P. Eckstein. (2020). Measurement of the useful field of view for single slices of different imaging modalities and targets. Journal of Medical Imaging. 7(2). 1–1. 12 indexed citations
15.
Lago, Miguel A., Miguel P. Eckstein, & Craig K. Abbey. (2019). A foveated channelized Hotelling search model predicts dissociations in human performance in 2D and 3D images. 12–12. 1 indexed citations
16.
Lago, Miguel A., Craig K. Abbey, Predrag R. Bakić, et al.. (2018). Interactions of lesion detectability and size across single-slice DBT and 3D DBT. PubMed. 10577. 32–32. 11 indexed citations
17.
Lago, Miguel A., Craig K. Abbey, & Miguel P. Eckstein. (2017). Foveated model observers to predict human performance in 3D images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10136. 101360P–101360P. 9 indexed citations
18.
Lago, Miguel A., et al.. (2015). Methodology based on genetic heuristics for in-vivo characterizing the patient-specific biomechanical behavior of the breast tissues. Expert Systems with Applications. 42(21). 7942–7950. 6 indexed citations
19.
Martínez‐Martínez, Francisco, Miguel A. Lago, María José Rupérez, & C. Monserrat. (2012). Analysis of several biomechanical models for the simulation of lamb liver behaviour using similarity coefficients from medical image. Computer Methods in Biomechanics & Biomedical Engineering. 16(7). 747–757. 9 indexed citations
20.
Martínez, Francisco M., et al.. (2011). NaRALap: augmented reality system for navigation in laparoscopic surgery. International Journal of Computer Assisted Radiology and Surgery. 6. 98–99.

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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