Javier Pascau

3.0k total citations
132 papers, 2.2k citations indexed

About

Javier Pascau is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Javier Pascau has authored 132 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Radiology, Nuclear Medicine and Imaging, 37 papers in Biomedical Engineering and 32 papers in Computer Vision and Pattern Recognition. Recurrent topics in Javier Pascau's work include Medical Imaging Techniques and Applications (30 papers), Advanced Radiotherapy Techniques (21 papers) and Anatomy and Medical Technology (19 papers). Javier Pascau is often cited by papers focused on Medical Imaging Techniques and Applications (30 papers), Advanced Radiotherapy Techniques (21 papers) and Anatomy and Medical Technology (19 papers). Javier Pascau collaborates with scholars based in Spain, United States and Germany. Javier Pascau's co-authors include Manuel Desco, Santiago Reig, Juan Domingo Gispert, Vicente Molina, Javier Sanz, María Luisa Soto‐Montenegro, A. Santos, José Antonio Calvo-Haro, Rubén Pérez‐Mañanes and P. Garcı́a-Barreno and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

In The Last Decade

Javier Pascau

127 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Javier Pascau Spain 29 687 437 367 359 312 132 2.2k
Jacques Felblinger France 30 1.7k 2.5× 839 1.9× 686 1.9× 182 0.5× 536 1.7× 182 3.9k
Richard D. Bucholz United States 29 490 0.7× 388 0.9× 321 0.9× 187 0.5× 642 2.1× 87 2.8k
Huaiqiang Sun China 22 1.1k 1.6× 654 1.5× 480 1.3× 235 0.7× 145 0.5× 73 2.0k
Thomas Lange Germany 32 590 0.9× 409 0.9× 527 1.4× 168 0.5× 1.5k 4.7× 163 4.0k
Ali R. Khan Canada 29 1.1k 1.6× 581 1.3× 281 0.8× 329 0.9× 138 0.4× 174 3.0k
Barrie Condon United Kingdom 30 1.1k 1.6× 366 0.8× 285 0.8× 190 0.5× 408 1.3× 82 2.7k
Dennis P. Hanson United States 17 662 1.0× 353 0.8× 132 0.4× 585 1.6× 124 0.4× 31 1.8k
Yakang Dai China 22 583 0.8× 444 1.0× 317 0.9× 62 0.2× 111 0.4× 121 1.7k
R. A. Robb United States 24 693 1.0× 155 0.4× 567 1.5× 97 0.3× 327 1.0× 76 2.4k
Alexander Rauscher Canada 36 2.5k 3.6× 472 1.1× 243 0.7× 245 0.7× 101 0.3× 131 3.8k

Countries citing papers authored by Javier Pascau

Since Specialization
Citations

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

Fields of papers citing papers by Javier Pascau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Javier Pascau

This figure shows the co-authorship network connecting the top 25 collaborators of Javier Pascau. A scholar is included among the top collaborators of Javier Pascau 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 Javier Pascau. Javier Pascau 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.
Pascau, Javier, et al.. (2025). Attention in surgical phase recognition for endoscopic pituitary surgery: Insights from real-world data. Computers in Biology and Medicine. 191. 110222–110222. 1 indexed citations
2.
3.
Tessier, Caroline, et al.. (2024). New Deep Learning-Based Approach for Dysphagia Assessment from Videofluoroscopy Swallowing Studies. SPIRE - Sciences Po Institutional REpository. 1–4. 1 indexed citations
4.
Ledezma, Agapito, et al.. (2023). ABANICCO: A New Color Space for Multi-Label Pixel Classification and Color Analysis. Sensors. 23(6). 3338–3338. 4 indexed citations
5.
Ungi, Tamás, et al.. (2023). Real-time integration between Microsoft HoloLens 2 and 3D Slicer with demonstration in pedicle screw placement planning. International Journal of Computer Assisted Radiology and Surgery. 18(11). 2023–2032. 7 indexed citations
6.
Cordero‐Grande, Lucilio, et al.. (2022). Breast Tumor Localization by Prone to Supine Landmark Driven Registration for Surgical Planning. IEEE Access. 10. 122901–122911. 1 indexed citations
7.
Calvo, Felipe A., Javier Serrano, Claudio V. Sole, et al.. (2022). Clinical feasibility of combining intraoperative electron radiation therapy with minimally invasive surgery: a potential for electron-FLASH clinical development. Clinical & Translational Oncology. 25(2). 429–439. 3 indexed citations
8.
Castelli, J., et al.. (2022). Deep Learning-Based Segmentation of Head and Neck Organs-at-Risk with Clinical Partially Labeled Data. Entropy. 24(11). 1661–1661. 6 indexed citations
9.
Calvo, Felipe A., Javier Serrano, Mauricio Cambeiro, et al.. (2022). Intra-Operative Electron Radiation Therapy: An Update of the Evidence Collected in 40 Years to Search for Models for Electron-FLASH Studies. Cancers. 14(15). 3693–3693. 10 indexed citations
10.
11.
Moreta-Martínez, Rafael, et al.. (2021). Augmented Reality as a Tool to Guide PSI Placement in Pelvic Tumor Resections. Sensors. 21(23). 7824–7824. 16 indexed citations
12.
Pérez‐Mañanes, Rubén, et al.. (2021). Patient-specific desktop 3D-printed guides for pelvic tumour resection surgery: a precision study on cadavers. International Journal of Computer Assisted Radiology and Surgery. 16(3). 397–406. 13 indexed citations
13.
Moreta-Martínez, Rafael, et al.. (2021). Combining Surgical Navigation and 3D Printing for Less Invasive Pelvic Tumor Resections. IEEE Access. 9. 133541–133551. 2 indexed citations
14.
Porras, Antonio R., Santiago Ochandiano, Roberto García‐Leal, et al.. (2021). Three-dimensional photography for intraoperative morphometric analysis in metopic craniosynostosis surgery. International Journal of Computer Assisted Radiology and Surgery. 16(2). 277–287. 8 indexed citations
15.
Ortuño, Juan E., et al.. (2020). A New Workflow for Image-Guided Intraoperative Electron Radiotherapy Using Projection-Based Pose Tracking. IEEE Access. 8. 137501–137516. 1 indexed citations
16.
Moreta-Martínez, Rafael, et al.. (2020). Desktop 3D Printing: Key for Surgical Navigation in Acral Tumors?. Applied Sciences. 10(24). 8984–8984. 4 indexed citations
17.
Guerrero‐Aspizua, Sara, et al.. (2020). Nonlinear Image Registration and Pixel Classification Pipeline for the Study of Tumor Heterogeneity Maps. Entropy. 22(9). 946–946. 2 indexed citations
18.
García-Ruiz, Alonso, et al.. (2018). Multicamera Optical Tracker Assessment for Computer Aided Surgery Applications. IEEE Access. 6. 64359–64370. 13 indexed citations
19.
Sole, Claudio V., et al.. (2016). ecancermedicalscience. ecancermedicalscience. 7. 339–339. 8 indexed citations
20.
García‐Vázquez, Verónica, Pedro Guerra, Felipe A. Calvo, et al.. (2016). Assessment of intraoperative 3D imaging alternatives for IOERT dose estimation. Zeitschrift für Medizinische Physik. 27(3). 218–231. 18 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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