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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Latest Journal Papers

• Bulant, CA; Blanco, PJ; Clausse, A; Guedes Bezerra, C; Lima, TP; Ávila, LFR, Lemos, PA; Feijóo, RA. Thermodynamic analogies for the characterization of 3D human coronary arteries. Biomedical Signal Processing and Control, v. 40, p. 163-170, 2018.
• Blanco, PJ; Müller, LO; Spence, JD. Blood pressure gradients in cerebral arteries: a clue to pathogenesis of cerebral small vessel disease. Stroke and Vascular Neurology, v. 3, p. e000087, 2017.
• Caiazzo, A; Caforio, F; Montecinos, G; Müller, LO; Blanco, PJ; Toro, EF. Assessment of reduced-order unscented Kalman filter for parameter identification in one-dimensional blood flow models using experimental data. International Journal for Numerical Methods in Biomedical Engineering, v. 33, p. e2843, 2017.
• Mansilla Alvarez, LA; Blanco, PJ; Bulant, CA; Dari, EA; Veneziani, A; Feijóo, RA. Transversally Enriched Pipe Element Method (TEPEM). An effective numerical approach for blood flow modeling. International Journal for Numerical Methods in Biomedical Engineering, v. 33, p. e2808, 2017.
• Ares, GD; Blanco, PJ; Urquiza, SA; Feijóo, RA. Identification of residual stresses in multi-layered arterial wall tissues using a variational framework. Computer Methods in Applied Mechanics and Engineering, v. 319, p. 287-313, 2017.
• Maso Talou, GD; Blanco, PJ; Larrabide, I; Guedes Bezerra, C; Lemos, PA; Feijóo, RA. Registration methods for IVUS: transversal and longitudinal transducer motion compensation. IEEE Transactions on Biomedical Engineering, v. 64, p. 890-903, 2017.
• Bulant, CA; Blanco, PJ; Müller, LO; Scharfstein, J; Svensjö, E. Computer-aided quantification of microvascular networks: Application to alterations due to pathological angiogenesis in the hamster. Microvascular Research, v. 112, p. 53-64, 2017.
• Bulant, CA; Blanco, PJ; Lima, TP; Assunção Jr, AN; Liberato, G; Parga, JR; Ávila, LFR; Pereira, AC; Feijóo, RA; Lemos, PA. A computational framework to characterize and compare the geometry of coronary networks. International Journal for Numerical Methods in Biomedical Engineering, v. 33, p. e02800, 2017.
• Bulant, CA; Blanco, PJ; Maso Talou, GD; Guedes Bezerra, C; Lemos, PA; Feijóo, RA. A head-to-head comparison between CT- and IVUS-derived coronary blood flow models. Journal of Biomechanics, v. 51, p. 65-76, 2017.
• Blanco, PJ; Clausse, A; Feijóo, RA. Homogenization of the Navier–Stokes equations by means of the Multi-scale Virtual Power Principle. Computer Methods in Applied Mechanics and Engineering, v. 315, p. 760-779, 2017.
• Bulant, CA; Blanco, PJ; Clausse, A; Assunção Jr, AN; Lima, TP; Ávila, LFR; Feijóo, RA; Lemos, PA. Association between three-dimensional vessel geometry and the presence of atherosclerotic plaques in the left anterior descending coronary artery of high-risk patients. Biomedical Signal Processing and Control, v. 31, p. 569-575, 2017.

Articles in Press

• Durka, MJ; Wong, IH; Kallmes, DF; Pasalic, D; Mut, F; Jagani, M; Blanco, PJ; Cebral, JR; Robertson, AM. A data driven approach for addressing the lack of flow waveform data in studies of cerebral arterial flow in older adults. Physiological Measurement, 2017.