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 postdoc researcher at ICVS, having been granted an FCT-funded junior post-doc 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 Focused Cardiac Ultrasound.
Overall, SQ (co-)authored 33 articles in peer-reviewed journals (11 as first/last author), 32 full proceedings in international conferences and 17 conference abstracts, totaling an accumulated impact factor of 147.38 (average IF = 4.5), >900 citations and an h-index of 17. His research outputs have also led to 1 Portuguese invention patent, 3 provisional patents and the commercial licensing of an image tracking software. SQ has also (co-)supervised the thesis of 3 Ph.D. (ongoing), 7 M.Sc. (4 ongoing) and 6 B.Sc. students.
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 postdoc researcher at ICVS, having been granted an FCT-funded junior post-doc 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 Focused Cardiac Ultrasound.
Overall, SQ (co-)authored 33 articles in peer-reviewed journals (11 as first/last author), 32 full proceedings in international conferences and 17 conference abstracts, totaling an accumulated impact factor of 147.38 (average IF = 4.5), >900 citations and an h-index of 17. His research outputs have also led to 1 Portuguese invention patent, 3 provisional patents and the commercial licensing of an image tracking software. SQ has also (co-)supervised the thesis of 3 Ph.D. (ongoing), 7 M.Sc. (4 ongoing) and 6 B.Sc. students.
Peer-reviewed publications:
– 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.
– 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.
– 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.
– 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.
– S. Queirós*, D. Barbosa*, B. Heyde, P. Morais, J. L. Vilaça, D. Friboulet, O. Bernard, J. D’hooge, “Fast automatic myocardial segmentation in 4D cine CMR datasets”, Medical image analysis, vol. 18, pp. 1115-1131, 2014. *Joint first authorship.
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.
– Provisional Portuguese Patent (PAT – 20211000016782), “Method and device for registration and tracking during a percutaneous procedure”, J. Gomes-Fonseca, J. L. Vilaça, S. Queirós, E. Lima, J. Correia-Pinto, 2021.
– Portuguese Invention Patent (PT 108184), “Método para determinação da posição e orientação tridimensional de implantes em imagens médicas”, A. H. J. Moreira, S. Queirós, N. F. Rodrigues, J. C. Fonseca, A. C. M. Pinho, J. L. Vilaça, 2016.
Focused cardiac ultrasound (FoCUS) refers to the use of ultrasound imaging to evaluate cardiac structure and function at the bedside by a treating physician. In recent years, FoCUS has become an indispensable first-line diagnostic tool, complementing…
This project aims to develop endoscopic, robotic and artificially intelligent surgical instruments that facilitate the performance of minimally invasive surgery. We are creating new surgical navigation systems using artificial intelligence…
Life and Health Sciences
Research Institute (ICVS)
School of Medicine,
University of Minho,
Campus de Gualtar
4710-057 Braga
Portugal
Copyright ©2022 ICVS. All Rights Reserved
Copyright ©2022 ICVS. All Rights Reserved
Life and Health Sciences
Research Institute (ICVS)
School of Medicine,
University of Minho,
Campus de Gualtar
4710-057 Braga
Portugal
Copyright ©2022 ICVS. All Rights Reserved
Life and Health Sciences
Research Institute (ICVS)
School of Medicine,
University of Minho,
Campus de Gualtar
4710-057 Braga
Portugal
