About HeMoLab

The HeMoLab (Hemodynamics Modeling Laboratory) group is, since 2006, a R&D group within the National Laboratory for Scientific Computing (LNCC/MCTI). Background areas of HeMoLab team members and collaborators are Engineering, Computer Science, Mathematics, Physiology, Cardiology, Anatomy and Physics. Core activities are related to the modeling and numerical simulation of physiological systems, more specifically the cardiovascular system. Research efforts are concentrated towards developing coupled and multiscale physical models based on variational foundations, as well as to develop and implement numerical approximations based on the Finite Element Method, the Finite Volume Method and the Lattice-Boltzmann Method. Blood flow models, fluid structure interaction, wave propagation phenomena, medical image processing, constitutive multiscale modeling and parameter identification procedures are some of the activities of the group. Software development targeting distributed computing systems is a continuous concern with the aim of popularizing modeling and simulation tools and facilitate their use in real large scale problems.


ADAN-WEB is a web application to provide users with extremely refined anatomical and functional data of the arterial network. This unprecedented dataset is based on the anatomical/medical domain knowledge, and has been developed in the HeMoLab group within the context of the INCT-MACC .

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ImageLab is a software for medical image processing designed to serve as an easy-to-use tool to aid cardiovascular research through the processing and segmentation of anatomical structures of interest from medical images. ImageLab can equally be used as a laboratory to aid the implementation of new algorithms and methods.

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New Book

Introduction to the Variational Formulation in Mechanics: Fundamentals and Applications, Published by Wiley. Available in 2020

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Latest Journal Papers

• Blanco, PJ; Bulant, CA; Bezerra, CG; Lemos, PA; García-García, HM. Simultaneous assessment of coronary stenosis relevance with automated computed tomography angiography and intravascular ultrasound analyses and fractional flow reserve. Coronary Artery Disease, v. 33, p. 25-30, 2022.
• Blanco, PJ; Ziemer, PGP; Bulant, CA; Ueki, Y; Bass, R; Räber, L; Lemos, PA; García-García, HM. Fully automated lumen and vessel contour segmentation in intravascular ultrasound datasets. Medical Image Analysis, v. 75, p. 102262, 2022.
• Cury, LFM; Maso Talou, GD; Younes-Ibrahim, M; Blanco, PJ. Parallel generation of extensive vascular networks with application to an archetypal human kidney model. Royal Society Open Science, v. 8, p. 210973, 2021.
• Fernandes, LG; Trenhago, PR; Feijóo, RA; Blanco, PJ. Integrated cardiorespiratory system model with short timescale control mechanisms. International Journal for Numerical Methods in Biomedical Engineering, v. 37, p. e3332, 2021.
• Blanco, PJ. Absorbable stents and the ever-evolving coronary hemodynamic landscape. Cardiovascular Revascularization Medicine, v. 29, p. 16-17, 2021.
• Blanco, PJ; Bulant, CA; Ares, GD; Lemos, PA; Feijóo, RA. A simple coronary blood flow model to study the collateral flow index. Biomechanics and Modeling in Mechanobiology, v. 20, p. 1365-1382, 2021.
• Rocha, FF; Blanco, PJ; Sánchez, PJ; Souza Neto, EA; Feijóo, RA. Damage-driven strain localisation in networks of fibres: A computational homogenisation approach. Computers and Structures, v. 255, p. 106635, 2021.
• Blanco, PJ; Bulant, CA; Guedes-Bezerra, C; Maso Talou, GD; Pinton, FA; Ziemer, PGP; Feijóo, RA; García‐García, HM; Lemos, PA. Coronary arterial geometry: a comprehensive comparison of two imaging modalities. International Journal for Numerical Methods in Biomedical Engineering, v. 37, p. e3442, 2021.
• Grinstein, J; Blanco, PJ; Bulant, CA; Torii, R; Bourantas, CV; Lemos, PA; García-García, HM. Left Ventricular Assist Device flow pattern analysis using computational fluid dynamics at the time of invasive hemodynamic ramp study: using patient-specific data to optimize the ramp study. The Journal of Heart and Lung Transplantation, v. 40, p. S450-S451, 2021.
• Grinstein, J; Blanco, PJ; Bulant, CA; Torii, R; Bourantas, CV; Lemos, PA; García-García, HM. Combining invasive cardiopulmonary exercise testing with computational fluid dynamics to better understand LVAD fluid mechanics during exercise. The Journal of Heart and Lung Transplantation, v. 40, p. S449, 2021.
• Maso Talou, GD; Safaei, S; Hunter, PJ; Blanco, PJ. Adaptive constrained constructive optimisation for complex vascularisation processes. Scientific Reports, V. 11, p. 6180, 2021.

Articles in Press

• Blanco, PJ; Vargas dos Santos, GH; Bulant, CA; Álvarez, LAM; Oliveira, FAP; Cunha-Lima, G; Lemos, PA. Scaling laws and the left main coronary artery bifurcation. A combination of geometric and simulation analyses. Medical Engineering & Physics, 2021.
• Spence, JD; Müller, LO; Blanco, PJ. How to identify which patients should not have a systolic blood pressure target of <120 mmHg. European Heart Journal, 2021.
• Biocca, N; Blanco, PJ; Caballero, DE; Gimenez, JM; Carr, GE; Urquiza, SA. A biologically-inspired mesh optimizer based on pseudo-material remodeling. Computational Mechanics, 2021.