15 resultados para Biomedical engineering|Medical imaging

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Estudi elaborat a partir d’una estada al Center Biomedical Engineering (CBE) del Massachussets Institute of Technology (MIT), durant els mesos de juliol i agost del 2005. S’investiga una metodologia amb l’objectiu d’obtenir biomaterials que puguin actuar de bastida en la interfície os/cartílag, afavorint la diferenciació i creixement cel·lular de cartílag ossificat que pugui actuar d’unió entre l’articulació i l’os. S’experimenta una metodologia per a establir quins són els péptids afavoridors de la formació de teixit ossi utilitzats en materials d’hidroxiapatita. Es conclou que la tecnologia desenvolupada permet disposar d’una plataforma per assajar l’estudi del signaling sobre cèl·lules embrionàries, que permeti desenvolupar materials amb més capacitat diferenciadora.

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The 1st chapter of this work presents the different experiments and collaborations in which I am involved during my PhD studies of Physics. Following those descriptions, the 2nd chapter is dedicated to how the radiation affects the silicon sensors, as well as some experimental measurements carried out at CERN (Geneve, Schwitzerland) and IFIC (Valencia, Spain) laboratories. Besides the previous investigation results, this chapter includes the most recent scientific papers appeared in the latest RD50 (Research & Development #50) Status Report, published in January 2007, as well as some others published this year. The 3rd and 4th are dedicated to the simulation of the electrical behavior of solid state detectors. In chapter 3 are reported the results obtained for the illumination of edgeless detectors irradiated at different fluences, in the framework of the TOSTER Collaboration. The 4th chapter reports about simulation design, simulation and fabrication of a novel 3D detector developed at CNM for ions detection in the future ITER fusion reactor. This chapter will be extended with irradiation simulations and experimental measurements in my PhD Thesis.

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In this project, we have investigated new ways of modelling and analysis of human vasculature from Medical images. The research was divided in two main areas: cerebral vasculature analysis and coronary arteries modeling. Regarding cerebral vasculature analysis, we have studed cerebral aneurysms, internal carotid and the Circle of Willis (CoW). Aneurysms are abnormal vessel enlargements that can rupture causing important cerebral damages or death. The understanding of this pathology, together with its virtual treatment, and image diagnosis and prognosis, includes identification and detailed measurement of the aneurysms. In this context, we have proposed two automatic aneurysm isolation method, to separate the abnormal part of the vessel from the healthy part, to homogenize and speed-up the processing pipeline usually employed to study this pathology, [Cardenes2011TMI, arrabide2011MedPhys]. The results obtained from both methods have been also compared and validatied in [Cardenes2012MBEC]. A second important task here the analysis of the internal carotid [Bogunovic2011Media] and the automatic labelling of the CoW, Bogunovic2011MICCAI, Bogunovic2012TMI]. The second area of research covers the study of coronary arteries, specially coronary bifurcations because there is where the formation of atherosclerotic plaque is more common, and where the intervention is more challenging. Therefore, we proposed a novel modelling method from Computed Tomography Angiography (CTA) images, combined with Conventional Coronary Angiography (CCA), to obtain realistic vascular models of coronary bifurcations, presented in [Cardenes2011MICCAI], and fully validated including phantom experiments in [Cardene2013MedPhys]. The realistic models obtained from this method are being used to simulate stenting procedures, and to investigate the hemodynamic variables in coronary bifurcations in the works submitted in [Morlachi2012, Chiastra2012]. Additionally, another preliminary work has been done to reconstruct the coronary tree from rotational angiography, and published in [Cardenes2012ISBI].

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Bone metastases are the result of a primary cancer invasion which spreads into the bone marrow through the lymphogenous or hematogenous pathways. Bone metastases are a common complication of cancer.The primary cancers that most frequently metastasize to bone are breast and prostate cancer (65 - 75 %) amongst many others (thyroid 42 %, lung 36 % or kidney 35 %) (Suva et al., 2011). Although the exact incidence of bone metastases is unknown given its dependence on the type of primary cancer, it is estimated that 350,000 people die of bone metastases annually in the United States.

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Ewing sarcoma or primitive neuroectodermal tumor (PNET) of bone is the second most common pediatric malignant bone tumor. The median age at diagnosis is 15 years and there is a male predilection of 1.5/1. The authors present the case of a 14-year-old boy with Ewing sarcoma situated on the left ninth rib which was being investigated for respiratory tract infection. Pleurisy is the most common misdiagnosis. Our case illustrates the importance of recognizing exceptional features when interpreting FDG PET or scintigraphy to prevent the misinterpretation of metastases as other etiologies, such as infection.

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Background Accurate automatic segmentation of the caudate nucleus in magnetic resonance images (MRI) of the brain is of great interest in the analysis of developmental disorders. Segmentation methods based on a single atlas or on multiple atlases have been shown to suitably localize caudate structure. However, the atlas prior information may not represent the structure of interest correctly. It may therefore be useful to introduce a more flexible technique for accurate segmentations. Method We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure. Results We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis. Conclusion CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.

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Con la creciente generación de resonancias magnéticas, los servicios de radiología necesitan aplicaciones que les faciliten el trabajo de acceso remoto a los datos y a las herramientas que utilicen para la extracción de datos para realizar sus diagnósticos. El objetivo de este proyecto es el de estudiar e integrar en la plataforma web del grupo de Imagen Médica del PIC llamada PICNIC (PIC NeuroImaging Center) un conjunto de aplicaciones para el estudio y procesamiento de neuroimagen con la implementación de herramientas software en la plataforma grid del PIC.

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La localització d'òrgans és un tòpic important en l'àmbit de la imatge mèdica per l'ajuda del tractament i diagnosi del càncer. Un exemple es pot trobar en la cal•libració de models farmacoquinètics. Aquesta pot ésser realitzada utilitzant un teixit de referència, on, per exemple en imatges de ressonància magnètica de pit, una correcta segmentació del múscul pectoral és necessària per a la detecció de signes de malignitat. Els mètodes de segmentació basat en atlas han estat altament avaluats en imatge de ressonància magnètica de cervell, obtenint resultats satisfactoris. En aquest projecte, en col•laboració amb el el Diagnostic Image Analysis Group de la Radboud University Nijmegen Medical Centre i la supervisió del Dr. N.Karssemeijer, es presenta la primera aproximació d'un mètode de segmentació basat en atlas per segmentar els diferents teixits visibles en imatges de ressonància magnètica (T1) del pit femení. L'atlas consisteix en 5 estructures (teixit greixòs, teixit dens, cor, pulmons i múscul pectoral) i ha estat utilitzat en un algorisme de segmentació Bayesià per tal de delinear les esmentades estructures. A més a més, s'ha dut a terme una comparació entre un mètode de registre global i un de local, utilitzats tant en la construcció de l'atlas com en la fase de segmentació, essent el primer el que ha presentat millors resultats en termes d'eficiència i precisió. Per a l'avaluació, s'ha dut a terme una comparació visual i numèrica entre les segmentacions obtingudes i les realitzades manualment pels experts col•laboradors. Pel que fa a la numèrica, s'ha emprat el coeficient de similitud de Dice ( mesura que dóna valors entre 0 i 1, on 0 significa no similitud i 1 similitud màxima) i s'ha obtingut una mitjana general de 0.8. Aquest resultat confirma la validesa del mètode presentat per a la segmentació d'imatges de ressonància magnètica del pit.

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In the last few years, there has been a growing focus on faster computational methods to support clinicians in planning stenting procedures. This study investigates the possibility of introducing computational approximations in modelling stent deployment in aneurysmatic cerebral vessels to achieve simulations compatible with the constraints of real clinical workflows. The release of a self-expandable stent in a simplified aneurysmatic vessel was modelled in four different initial positions. Six progressively simplified modelling approaches (based on Finite Element method and Fast Virtual Stenting – FVS) have been used. Comparing accuracy of the results, the final configuration of the stent is more affected by neglecting mechanical properties of materials (FVS) than by adopting 1D instead of 3D stent models. Nevertheless, the differencesshowed are acceptable compared to those achieved by considering different stent initial positions. Regarding computationalcosts, simulations involving 1D stent features are the only ones feasible in clinical context.

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Nanoscale electron transport through the purple membrane monolayer, a two-dimensional crystal lattice of the transmembrane protein bacteriorhodopsin, is studied by conductive atomic force microscopy. We demonstrate that the purple membrane exhibits nonresonant tunneling transport, with two characteristic tunneling regimes depending on the applied voltage (direct and Fowler-Nordheim). Our results show that the purple membrane can carry significant current density at the nanometer scale, several orders of magnitude larger than previously estimated by macroscale measurements.

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The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.

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We present a 53-year-old man with a vocal cord paralysis observed as a primary manifestation of lung carcinoma. Tc-99m MDP whole body bone scan were performed and resulted a normal scintiscan. The bone scan does not revealed suspicious foci of uptake. The possibility of bone metastasis was taken into consideration. A whole body F18-FDG-PET scan showed intense uptake in the left upper lung corresponding to the primary tumor. A bronchial biopsy confirmed infiltration by small cell lung carcinoma (SCLC). SCLC is composed of poorly differentiated, rapidly growing cells with disease usually occurring centrally rather than peripherally. It metastasizes early. The whole-body F18-FDG-PET scan clearly demonstrated a focus of increased uptake in the second lumbar vertebral body suspicious for osteolytic metastasis. A lytic bone metastasis was confirmed by MRI. The patient then received therapy and underwent follow up abdominal CT. The scan showed blastic changes in the L2 vertebra suggesting response to treatment.

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Image registration has been proposed as an automatic method for recovering cardiac displacement fields from Tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the -entropy (H ) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p < 0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presentsan interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging.

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Engineered nanomaterials are emerging functional materials with technologically interesting properties and a wide range of promising applications, such as drug delivery devices, medical imaging and diagnostics, and various other industrial products. However, concerns have been expressed about the risks of such materials and whether they can cause adverse effects. Studies of the potential hazards of nanomaterials have been widely performed using cell models and a range of in vitro approaches. In the present review, we provide a comprehensive and critical literature overview on current in vitro toxicity test methods that have been applied to determine the mechanisms underlying the cytotoxic effects induced by the nanostructures. The small size, surface charge, hydrophobicity and high adsorption capacity of nanomaterial allow for specific interactions within cell membrane and subcellular organelles, which in turn could lead to cytotoxicity through a range of different mechanisms. Finally, aggregating the given information on the relationships of nanomaterial cytotoxic responses with an understanding of its structure and physicochemical properties may promote the design of biologically safe nanostructures.

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The multidimensional process of physical, psychological, and social change produced by population ageing affects not only the quality of life of elderly people but also of our societies. Some dimensions of population ageing grow and expand over time (e.g. knowledge of the world events, or experience in particular situations), while others decline (e.g. reaction time, physical and psychological strength, or other functional abilities like reduced speed and tiredness). Information and Communication Technologies (ICTs) can help elderly to overcome possible limitations due to ageing. As a particular case, biometrics can allow the development of new algorithms for early detection of cognitive impairments, by processing continuous speech, handwriting or other challenged abilities. Among all possibilities, digital applications (Apps) for mobile phones or tablets can allow the dissemination of such tools. In this article, after presenting and discussing the process of population ageing and its social implications, we explore how ICTs through different Apps can lead to new solutions for facing this major demographic challenge.