Accurate segmentation of the prostate and organs at risk in computed tomography (CT) images is a crucial step for radiotherapy planning. Manual segmentation, as performed nowadays, is a time consuming process and prone to errors due to the a high intra- and inter-expert variability. This paper introduces a new automatic method for prostate, rectum and bladder segmentation in planning CT using a geometrical shape model under a Bayesian framework. A set of prior organ shapes are first built by applying principal component analysis to a population of manually delineated CT images. Then, for a given individual, the most similar shape is obtained by mapping a set of multi-scale edge observations to the space of organs with a customized likelihood function. Finally, the selected shape is locally deformed to adjust the edges of each organ. Experiments were performed with real data from a population of 116 patients treated for prostate cancer. The data set was split in training and test groups, with 30 and 86 patients, respectively. Results show that the method produces competitive segmentations w.r.t standard methods (averaged dice = 0.91 for prostate, 0.94 for bladder, 0.89 for rectum) and outperforms the majority-vote multi-atlas approaches (using rigid registration, free-form deformation and the demons algorithm).
Recibido el 9 de octubre de 2013. Aceptado para su publicación el 12 de enero de 2014. RESUMEN Objetivo: Estimar la asociación entre síntomas depresivos y ansiosos con factores sociodemográficos, académicos, conductuales y familiares entre estudiantes universitarios de Cartagena, Colombia. Diseño del estudio: Estudio transversal.
ResumenLa marcha humana es el resultado de la compleja interacción entre varios subsistemas: neuromuscular, músculo-tendinoso y osteoarticular, que trabajan coordinadamente para generan la dinámica corporal necesaria para el desplazamiento bípedo. En la rutina clínica, el estudio de la marcha es la base de la identificación de trastornos patológicos, facilitando su diagnóstico, tratamiento y seguimiento. Tradicionalmente este análisis determina el conjunto de patrones que describen la dinámica del sistema. Sin embargo, éste análisis es insuficiente para evaluar algunos movimientos, sobre todo para los estadios tempranos de casi todos los movimientos patológicos. El desarrollo de diferentes modelos normales y patológicos ha permitido establecer diferencias objetivas para cada una de estas situaciones. En este artículo se hace una revisión de los modelos que describen la dinámica de la marcha humana normal y patológica, inspirados en la morfo-fisiología del sistema locomotor. Además, se hace un análisis sobre la efectividad de los modelos propuestos en la literatura para describir comportamientos patológicos.Palabras clave: modelos teóricos, marcha, biomecánica, ingeniería biomédica
THEORETICAL AND COMPUTATIONAL ANALYSIS OF NORMAL AND PATHOLOGICAL GAIT: A REVIEW
AbstractThe human gait is the result of complex interactions between several sub-systems: neuromuscular, musculo-tendinous and osteo-articular, which work together to generate the body dynamics necessary to describe the bipedal movement. In the clinical routine, the gait analysis is the main element for identifying pathological disorders, supporting the diagnosis and facilitating a proper follow up. Traditionally, this analysis aims to establish the set of patterns that describe the dynamics of the system. However, this analysis is insufficient for some movements, especially for early stages of almost every pathological movement. The development of normal and pathological models has allowed to demostrate objective differences for each of these situations. In this article we present a summary of the models that describe the dynamics of the normal and pathological human gait, inspired by the morpho-physiology of the locomotor system. Furthermore, we perform an analysis of the effectiveness of the proposed models in the literature.
Recibido el 17 de marzo de 2014. Aceptado para su publicación el 1 de abril de 2014. RESUMEN Objetivo: Describir los conocimientos, actitudes y prácticas sobre maltrato infantil en estudiantes de odontología en una universidad pública de Cartagena, Colombia. Diseño del estudio: Estudio descriptivo.
A new method for automatic analysis and characterization of recorded hummingbird wing motion is proposed. The method starts by computing a multiscale dense optical flow field, which is used to segment the wings, i.e., pixels with larger velocities. Then, the kinematic and deformation of the wings were characterized as a temporal set of global and local measures: a global angular acceleration as a time function of each wing and a local acceleration profile that approximates the dynamics of the different wing segments. Additionally, the variance of the apparent velocity orientation estimates those wing foci with larger deformation. Finally a local measure of the orientation highlights those regions with maximal deformation. The approach was evaluated in a total of 91 flight cycles, captured using three different setups. The proposed measures follow the yaw turn hummingbird flight dynamics, with a strong correlation of all computed paths, reporting a standard deviation of [Formula: see text] and [Formula: see text] for the global angular acceleration and the global wing deformation respectively.
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