Sandro Queirós

  • Biomedical engineering
  • Medical image processing
  • Computer-aided diagnosis
  • Cardiac Imaging
  • Artificial Intelligence

Sandro Queirós (SQ) graduated in Biomedical Engineering in 2013 by the University of Minho (Portugal). In 2018, he completed a joint Ph.D. degree in Biomedical Engineering by the University of Minho (Portugal) and in Biomedical Sciences by KU Leuven (Belgium). Since 2018, SQ is a full-time researcher at ICVS, having been granted an FCT-funded junior research position in 2020.
Throughout his research career, Sandro has been mainly interested in the development of novel medical imaging processing solutions to help clinicians in the diagnosis and treatment of diseases. Specifically, his work has been focused primarily on cardiovascular diseases – the leading cause of death in the world. He has been the leading developer of novel image processing methodologies for cardiac function quantification, as well as novel technological solutions for preoperative planning, intraoperative guidance, and postoperative evaluation of transcatheter heart interventions. More recently, his work aims at developing novel artificial intelligent solutions for automatic medical training and diagnosis in echocardiography.
Overall, SQ (co-)authored 40 peer-reviewed articles, 39 full proceedings, and 29 conference abstracts, totaling an accumulated IF of 184, >1300 citations and an h-index of 21. His research outputs have also led to 2 international and 1 Portuguese invention patents, 2 provisional patents and the commercial licensing of an image tracking software. SQ has also (co-)supervised the thesis of 4 Ph.D. (ongoing), 10 M.Sc. (3 ongoing) and 6 B.Sc. students.

Sandro Queirós

  • Biomedical engineering
  • Medical image processing
  • Computer-aided diagnosis
  • Cardiac Imaging
  • Artificial Intelligence

Sandro Queirós (SQ) graduated in Biomedical Engineering in 2013 by the University of Minho (Portugal). In 2018, he completed a joint Ph.D. degree in Biomedical Engineering by the University of Minho (Portugal) and in Biomedical Sciences by KU Leuven (Belgium). Since 2018, SQ is a full-time researcher at ICVS, having been granted an FCT-funded junior research position in 2020.
Throughout his research career, Sandro has been mainly interested in the development of novel medical imaging processing solutions to help clinicians in the diagnosis and treatment of diseases. Specifically, his work has been focused primarily on cardiovascular diseases – the leading cause of death in the world. He has been the leading developer of novel image processing methodologies for cardiac function quantification, as well as novel technological solutions for preoperative planning, intraoperative guidance, and postoperative evaluation of transcatheter heart interventions. More recently, his work aims at developing novel artificial intelligent solutions for automatic medical training and diagnosis in echocardiography.
Overall, SQ (co-)authored 40 peer-reviewed articles, 39 full proceedings, and 29 conference abstracts, totaling an accumulated IF of 184, >1300 citations and an h-index of 21. His research outputs have also led to 2 international and 1 Portuguese invention patents, 2 provisional patents and the commercial licensing of an image tracking software. SQ has also (co-)supervised the thesis of 4 Ph.D. (ongoing), 10 M.Sc. (3 ongoing) and 6 B.Sc. students.

Scientific Highlights

Peer-reviewed publications:
– J. Freitas, J. Gomes-Fonseca, A.C. Tonelli, J. Correia-Pinto, J. C. Fonseca, S. Queirós, “Automatic multi-view pose estimation in focused cardiac ultrasound”, Medical Image Analysis, vol. 94, pp. 103146, 2024. DOI: 10.1016/j.media.2024.103146
– B. Silva, I. Pessanha, J. Correia-Pinto, J. C. Fonseca, S. Queirós, “Automatic assessment of Pectus Excavatum severity from CT images using deep learning”, IEEE Journal of Biomedical Health Informatics, vol. 26, pp. 324-333, 2022. DOI: 10.1109/JBHI.2021.3090966
– S. Queirós, P. Morais, D. Barbosa, J. C. Fonseca, J. L. Vilaça, J. D’hooge, “MITT: Medical Image Tracking Toolbox”, IEEE Transactions on Medical Imaging, vol. 37, pp. 2547-2557, 2018. DOI: 10.1109/TMI.2018.2840820
– S. Queirós, P. Morais, C. Dubois, J-U Voigt, W. Fehske, A. Kuhn, T. Achenbach, J. C. Fonseca, J. L. Vilaça, J. D’hooge, “Validation of a novel software tool for automatic aortic annular sizing in three-dimensional transesophageal echocardiographic images”, Journal of the American Society of Echocardiography, vol. 31, pp. 515-525.e5, 2018. DOI: 10.1016/j.echo.2018.01.007
– S. Queirós, A. Papachristidis, D. Barbosa, K. C. Theodoropoulos, J. C. Fonseca, M. J. Monaghan, J. L. Vilaça, J. D’hooge, “Aortic valve tract segmentation from 3D-TEE using shape-based B-spline Explicit Active Surfaces”, IEEE Transactions on Medical Imaging, vol. 35(9), pp. 2015-2025, 2016. DOI: 10.1109/TMI.2016.2544199
– S. Queirós, D. Barbosa, J. Engvall, T. Ebbers, E. Nagel, S. I. Sarvari, P. Claus, J. C. Fonseca, J. L. Vilaça, J. D’hooge, “Multi-centre validation of an automatic algorithm for fast 4D myocardial segmentation in cine CMR datasets”, European Heart Journal – Cardiovascular Imaging, vol. 17, pp. 1118-1127, 2016. DOI: 10.1093/ehjci/jev247

Software Licensing/Intelectual Property:
– Licensing of an image tracking algorithm for commercial exploitation by an international company, to be used for cardiac magnetic resonance image sequences (2022).
– Provisional Portuguese Patent (PT 117845), “Device and method for obtaining a full-surface estimate of an organ from a received partial anatomical point cloud”, S. Queirós, J. Gomes-Fonseca, J. L. Vilaça, E. Lima, J. Correia-Pinto, 2022.
– International Invention Patent (WO2022229937A1), “Method and device for registration and tracking during a percutaneous procedure”, J. Gomes-Fonseca, J. L. Vilaça, S. Queirós, E. Lima, J. Correia-Pinto, 2022.
– International Invention Patent (WO2022229916A1), “Method and device for generating an uncertainty map for guided percutaneous procedures”, J. Gomes-Fonseca, J. L. Vilaça, S. Queirós, E. Lima, J. Correia-Pinto, 2022.

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