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)
In this paper we present a management model to deal with the problem of tracking a large number of features during long image sequences. Some usual difficulties are related to this problem: features may be temporarily occluded or might even have disappeared definitively; the computational cost involved should always be reduced to the strictly necessary. The(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)
In this paper we address the problem of tracking feature points along image sequences. To analyze the undergoing movement we use a common approach based on Kalman filtering which performs the estimation and correction of the feature point's movement in every image frame. The criterion proposed to establish correspondences, between the group of estimates in(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)
Computer analysis of objects' movement in image sequences is a very complex problem, as it usually involves tasks for automatic detection, matching, tracking and deformation estimation. However, this computational analysis has a wide range of important applications; for instance, in surveillance systems, clinical analysis of human gait, objects recognition(More)