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Carles Sanchez, Oriol Ramos Terrades, Patricia Marquez, Enric Marti, J.Roncaries, & Debora Gil. (2015). Automatic evaluation of practices in Moodle for Self Learning in Engineering. JOTSE - Journal of Technology and Science Education, 97–106.
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Aura Hernandez-Sabate, Lluis Albarracin, & F. Javier Sanchez. (2020). Graph-Based Problem Explorer: A Software Tool to Support Algorithm Design Learning While Solving the Salesperson Problem. MATH - Mathematics, 1595.
Abstract: In this article, we present a sequence of activities in the form of a project in order to promote
learning on design and analysis of algorithms. The project is based on the resolution of a real problem, the salesperson problem, and it is theoretically grounded on the fundamentals of mathematical modelling. In order to support the students’ work, a multimedia tool, called Graph-based Problem Explorer (GbPExplorer), has been designed and refined to promote the development of computer literacy in engineering and science university students. This tool incorporates several modules to allow coding different algorithmic techniques solving the salesman problem. Based on an educational design research along five years, we observe that working with GbPExplorer during the project provides students with the possibility of representing the situation to be studied in the form of graphs and analyze them from a computational point of view.
Keywords: STEM education; Project-based learning; Coding; software tool
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Aura Hernandez-Sabate, Debora Gil, Eduard Fernandez-Nofrerias, Petia Radeva, & Enric Marti. (2009). Approaching Artery Rigid Dynamics in IVUS. TMI - IEEE Transactions on Medical Imaging, 28(11), 1670–1680.
Abstract: Tissue biomechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation. Since intravascular ultrasound (IVUS) sequences allow visualizing vessel morphology and reflect its dynamics, this technique represents a useful tool for evaluation of tissue mechanical properties. Image misalignment introduced by vessel-catheter motion is a major artifact for a proper tracking of tissue deformation. In this work, we focus on compensating and assessing IVUS rigid in-plane motion due to heart beating. Motion parameters are computed by considering both the vessel geometry and its appearance in the image. Continuum mechanics laws serve to introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; whereas results in in vivo pullbacks show the reliability of the presented methodologies in clinical cases.
Keywords: Fourier analysis; intravascular ultrasound (IVUS) dynamics; longitudinal motion; quality measures; tissue deformation.
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Carles Sanchez, Jorge Bernal, F. Javier Sanchez, Antoni Rosell, Marta Diez-Ferrer, & Debora Gil. (2015). Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy. IJCAR - International Journal of Computer Assisted Radiology and Surgery, 10(6), 935–945.
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Aura Hernandez-Sabate, Debora Gil, Jaume Garcia, & Enric Marti. (2011). Image-based Cardiac Phase Retrieval in Intravascular Ultrasound Sequences. T-UFFC - IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 58(1), 60–72.
Abstract: Longitudinal motion during in vivo pullbacks acquisition of intravascular ultrasound (IVUS) sequences is a major artifact for 3-D exploring of coronary arteries. Most current techniques are based on the electrocardiogram (ECG) signal to obtain a gated pullback without longitudinal motion by using specific hardware or the ECG signal itself. We present an image-based approach for cardiac phase retrieval from coronary IVUS sequences without an ECG signal. A signal reflecting cardiac motion is computed by exploring the image intensity local mean evolution. The signal is filtered by a band-pass filter centered at the main cardiac frequency. Phase is retrieved by computing signal extrema. The average frame processing time using our setup is 36 ms. Comparison to manually sampled sequences encourages a deeper study comparing them to ECG signals.
Keywords: 3-D exploring; ECG; band-pass filter; cardiac motion; cardiac phase retrieval; coronary arteries; electrocardiogram signal; image intensity local mean evolution; image-based cardiac phase retrieval; in vivo pullbacks acquisition; intravascular ultrasound sequences; longitudinal motion; signal extrema; time 36 ms; band-pass filters; biomedical ultrasonics; cardiovascular system; electrocardiography; image motion analysis; image retrieval; image sequences; medical image processing; ultrasonic imaging
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