Raquel Ramos Pinho

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Spinal lamina I receives nociceptive primary afferent input to project through diverse ascending pathways, including the anterolateral tract (ALT). Large projection neurons (PNs) form only a few per cent of the cell population in this layer, and little is known about their local input from other lamina I neurons. We combined single-cell imaging in the(More)
Spinal lamina I is a key area for relaying and integrating information from nociceptive primary afferents with various other sources of inputs. Although lamina I projection neurons have been intensively studied, much less attention has been given to local-circuit neurons (LCNs), which form the majority of the lamina I neuronal population. In this work the(More)
This paper presents a physics-based approach to obtain 2D or 3D dynamic pedobarography transitional objects from two given images (2D or 3D). With the used methodology, we match nodes of the input objects by using modal matching, improved with optimization techniques, and solve the Lagrangian dynamic equilibrium equation to obtain the intermediate shapes.(More)
The pathogenesis of many neurodegenerative disorders arises in association with the misfolding and accumulation of a wide variety of proteins. Much emphasis has been placed on understanding the nature of these protein accumulations, including their composition, the process by which they are formed and the physiological impact they impose at cellular and,(More)
This paper addresses the problem of tracking feature points along image sequences to analyze the undergoing human movement. An approach based on Kalman filtering performs the estimation and correction of the feature point's movement in every image frame, and optimizes the incorporation of the measured data in order to establish the best global(More)
We address the problem of tracking efficiently feature points along image sequences. To estimate the undergoing movement we use an approach based on Kalman filtering which performs the prediction and correction of the features movement in every image frame. In this paper measured data is incorporated by optimizing the global correspondence set based on(More)
This paper presents a methodology to do morphing between image represented objects, attending to their physical properties. It can be used amongst images of different objects, or otherwise, between different images of the same object.According to the used methodology the given objects are modelled by the Finite Element Method, and some nodes are matched by(More)
This paper presents a physical approach to simulate objects deformation in images. To physically model the given objects the finite element method is used, and to match the objects' nodes modal analysis is considered. The desired displacement field is estimated through the dynamic equilibrium equation. To solve this differential equation different(More)
Tracking features along image sequences has been a long-standing problem in Computational Vision, as no known framework has been able to demonstrate its robustness to all kinds of changeling problems that may occur (for instance, image sequences with complex motions, cluttered scenes, noisy data, oc-clusions, topology variations or high number of mage(More)
This work addresses the problem of tracking feature points along image sequences. In order to analyze the undergoing movement, an approach based on the Kalman filtering technique has been used, which basically carries out the estimation and correction of the features' movement in every image frame. So as to integrate the measurements obtained from each(More)