950 resultados para image processing--digital techniques
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Black-blood MR coronary vessel wall imaging may become a powerful tool for the quantitative and noninvasive assessment of atherosclerosis and positive arterial remodeling. Although dual-inversion recovery is currently the gold standard, optimal lumen-to-vessel wall contrast is sometimes difficult to obtain, and the time window available for imaging is limited due to competing requirements between blood signal nulling time and period of minimal myocardial motion. Further, atherosclerosis is a spatially heterogeneous disease, and imaging at multiple anatomic levels of the coronary circulation is mandatory. However, this requirement of enhanced volumetric coverage comes at the expense of scanning time. Phase-sensitive inversion recovery has shown to be very valuable for enhancing tissue-tissue contrast and for making inversion recovery imaging less sensitive to tissue signal nulling time. This work enables multislice black-blood coronary vessel wall imaging in a single breath hold by extending phase-sensitive inversion recovery to phase-sensitive dual-inversion recovery, by combining it with spiral imaging and yet relaxing constraints related to blood signal nulling time and period of minimal myocardial motion.
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Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.
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We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.
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Reconstruction of important parameters such as femoral offset and torsion is inaccurate, when templating is based on plain x-rays. We evaluate intraoperative reproducibility of pre-operative CT-based 3D-templating in a consecutive series of 50 patients undergoing primary cementless THA through an anterior approach. Pre-operative planning was compared to a postoperative CT scan by image fusion. The implant size was correctly predicted in 100% of the stems, 94% of the cups and 88% of the heads (length). The difference between the planned and the postoperative leg length was 0.3 + 2.3 mm. Values for overall offset, femoral anteversion, cup inclination and anteversion were 1.4 mm ± 3.1, 0.6° ± 3.3°, -0.4° ± 5° and 6.9° ± 11.4°, respectively. This planning allows accurate implant size prediction. Stem position and cup inclination are accurately reproducible.
Resumo:
BACKGROUND: In chronic kidney disease (CKD) patients, the intake of calcium-based phosphate binders is associated with a marked progression of coronary artery and aortic calcification, in contrast to patients receiving calcium-free phosphate binders. The aim of this study was to reexamine the role of calcium carbonate in vascular calcification and to analyse its effect on aortic calcification-related gene expression in chronic renal failure (CRF). METHODS: Mice deficient in apolipoprotein E underwent either sham operation or subtotal nephrectomy to create CRF. They were then randomly assigned to one of the three following groups: a control non-CRF group and a CRF group fed on standard diet, and a CRF group fed on calcium carbonate enriched diet, for a period of 8 weeks. Aortic atherosclerotic plaque and calcification were evaluated using quantitative morphologic image processing. Aortic gene and protein expression was examined using immunohistochemistry and Q-PCR methods. RESULTS: Calcium carbonate supplementation was effective in decreasing serum phosphorus but was associated with a higher serum calcium concentration. Compared with standard diet, calcium carbonate enriched diet unexpectedly induced a significant decrease of both plaque (p<0.05) and non-plaque-associated calcification surface (p<0.05) in CRF mice. It also increased osteopontin (OPN) protein expression in atherosclerotic lesion areas of aortic root. There was also a numerical increase in OPN and osteoprotegerin gene expression in total thoracic aorta but the difference did not reach the level of significance. Finally, calcium carbonate did not change the severity of atherosclerotic lesions. CONCLUSION: In this experimental model of CRF, calcium carbonate supplementation did not accelerate but instead decreased vascular calcification. If our observation can be extrapolated to humans, it appears to question the contention that calcium carbonate supplementation, at least when given in moderate amounts, necessarily enhances vascular calcification. It is also compatible with the hypothesis of a preponderant role of phosphorus over that of calcium in promoting vascular calcification in CRF.
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The distribution of parvalbumin (PV), calretinin (CR), and calbindin (CB) immunoreactive neurons was studied with the help of an image analysis system (Vidas/Zeiss) in the primary visual area 17 and associative area 18 (Brodmann) of Alzheimer and control brains. In neither of these areas was there a significant difference between Alzheimer and control groups in the mean number of PV, CR, or CB immunoreactive neuronal profiles, counted in a cortical column going from pia to white matter. Significant differences in the mean densities (numbers per square millimeter of cortex) of PV, CR, and CB immunoreactive neuronal profiles were not observed either between groups or areas, but only between superficial, middle, and deep layers within areas 17 and 18. The optical density of the immunoreactive neuropil was also similar in Alzheimer and controls, correlating with the numerical density of immunoreactive profiles in superficial, middle, and deep layers. The frequency distribution of neuronal areas indicated significant differences between PV, CR, and CB immunoreactive neuronal profiles in both areas 17 and 18, with more large PV than CR and CB positive profiles. There were also significantly more small and less large PV and CR immunoreactive neuronal profiles in Alzheimer than in controls. Our data show that, although the brain pathology is moderate to severe, there is no prominent decrease of PV, CR and CB positive neurons in the visual cortex of Alzheimer brains, but only selective changes in neuronal perikarya.
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AIM: To determine the long-term prognostic value of SPECT myocardial perfusion imaging (MPI) for the occurrence of cardiovascular events in diabetic patients. PATIENTS, METHODS: SPECT MPI of 210 consecutive Caucasian diabetic patients were analysed using Kaplan-Meier event-free survival curves and independent predictors were determined by Cox multivariate analyses. RESULTS: Follow-up was complete in 200 (95%) patients with a median period of 3.0 years (0.8-5.0). The population was composed of 114 (57%) men, age 65 +/- 10 years, 181 (90.5%) type 2 diabetes mellitus, 50 (25%) with a history of coronary artery disease (CAD) and 98 (49%) presenting chest pain prior to MPI. The prevalence of abnormal MPI was 58%. Patients with a normal MPI had neither cardiac death, nor myocardial infarction, independently of a history of coronary artery disease or chest pain. Among the independent predictors of cardiac death and myocardial infarction, the strongest was abnormal MPI (p < 0.0001), followed by history of CAD (Hazard Ratio (HR) = 15.9; p = 0.0001), diabetic retinopathy (HR = 10.0; p = 0.001) and inability to exercise (HR = 7.7; p = 0.02). Patients with normal MPI had a low revascularisation rate of 2.4% during the follow-up period. Compared to normal MPI, cardiovascular events increased 5.2 fold for reversible defects, 8.5 fold for fixed defects and 20.1 fold for the association of both defects. CONCLUSION: Diabetic patients with normal MPI had an excellent prognosis independently of history of CAD. On the opposite, an abnormal MPI led to a >5-fold increase in cardiovascular events. This emphasizes the value of SPECT MPI in predicting and risk-stratifying cardiovascular events in diabetic patients.
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Computed tomography (CT) is used increasingly to measure liver volume in patients undergoing evaluation for transplantation or resection. This study is designed to determine a formula predicting total liver volume (TLV) based on body surface area (BSA) or body weight in Western adults. TLV was measured in 292 patients from four Western centers. Liver volumes were calculated from helical computed tomographic scans obtained for conditions unrelated to the hepatobiliary system. BSA was calculated based on height and weight. Each center used a different established method of three-dimensional volume reconstruction. Using regression analysis, measurements were compared, and formulas correlating BSA or body weight to TLV were established. A linear regression formula to estimate TLV based on BSA was obtained: TLV = -794.41 + 1,267.28 x BSA (square meters; r(2) = 0.46; P <.0001). A formula based on patient weight also was derived: TLV = 191.80 + 18.51 x weight (kilograms; r(2) = 0.49; P <.0001). The newly derived TLV formula based on BSA was compared with previously reported formulas. The application of a formula obtained from healthy Japanese individuals underestimated TLV. Two formulas derived from autopsy data for Western populations were similar to the newly derived BSA formula, with a slight overestimation of TLV. In conclusion, hepatic three-dimensional volume reconstruction based on helical CT predicts TLV based on BSA or body weight. The new formulas derived from this correlation should contribute to the estimation of TLV before liver transplantation or major hepatic resection.
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OBJECTIVE: Surface magnetic resonance imaging (MRI) for aortic plaque assessment is limited by the trade-off between penetration depth and signal-to-noise ratio (SNR). For imaging the deep seated aorta, a combined surface and transesophageal MRI (TEMRI) technique was developed 1) to determine the individual contribution of TEMRI and surface coils to the combined signal, 2) to measure the signal improvement of a combined surface and TEMRI over surface MRI, and 3) to assess for reproducibility of plaque dimension analysis. METHODS AND RESULTS: In 24 patients six black blood proton-density/T2-weighted fast-spin echo images were obtained using three surface and one TEMRI coil for SNR measurements. Reproducibility of plaque dimensions (combined surface and TEMRI) was measured in 10 patients. TEMRI contributed 68% of the signal in the aortic arch and descending aorta, whereas the overall signal gain using the combined technique was up to 225%. Plaque volume measurements had an intraclass correlation coefficient of as high as 0.97. CONCLUSION: Plaque volume measurements for the quantification of aortic plaque size are highly reproducible for combined surface and TEMRI. The TEMRI coil contributes considerably to the aortic MR signal. The combined surface and TEMRI approach improves aortic signal significantly as compared to surface coils alone. CONDENSED ABSTRACT: Conventional MRI aortic plaque visualization is limited by the penetration depth of MRI surface coils and may lead to suboptimal image quality with insufficient reproducibility. By combining a transesophageal MRI (TEMRI) with surface MRI coils we enhanced local and overall image SNR for improved image quality and reproducibility.
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A crucial method for investigating patients with coronary artery disease (CAD) is the calculation of the left ventricular ejection fraction (LVEF). It is, consequently, imperative to precisely estimate the value of LVEF--a process that can be done with myocardial perfusion scintigraphy. Therefore, the present study aimed to establish and compare the estimation performance of the quantitative parameters of the reconstruction methods filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM). METHODS: A beating-heart phantom with known values of end-diastolic volume, end-systolic volume, and LVEF was used. Quantitative gated SPECT/quantitative perfusion SPECT software was used to obtain these quantitative parameters in a semiautomatic mode. The Butterworth filter was used in FBP, with the cutoff frequencies between 0.2 and 0.8 cycles per pixel combined with the orders of 5, 10, 15, and 20. Sixty-three reconstructions were performed using 2, 4, 6, 8, 10, 12, and 16 OSEM subsets, combined with several iterations: 2, 4, 6, 8, 10, 12, 16, 32, and 64. RESULTS: With FBP, the values of end-diastolic, end-systolic, and the stroke volumes rise as the cutoff frequency increases, whereas the value of LVEF diminishes. This same pattern is verified with the OSEM reconstruction. However, with OSEM there is a more precise estimation of the quantitative parameters, especially with the combinations 2 iterations × 10 subsets and 2 iterations × 12 subsets. CONCLUSION: The OSEM reconstruction presents better estimations of the quantitative parameters than does FBP. This study recommends the use of 2 iterations with 10 or 12 subsets for OSEM and a cutoff frequency of 0.5 cycles per pixel with the orders 5, 10, or 15 for FBP as the best estimations for the left ventricular volumes and ejection fraction quantification in myocardial perfusion scintigraphy.
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Mitjançant les tècniques de visió per computador aquest projecte pretén desenvolupar una aplicació capaç de segmentar la pell, detectar nevus (pigues i altres taques) i poder comparar imatges de pacients amb risc de contreure melanoma preses en moments diferents. Aquest projecte pretén oferir diferents eines informàtiques als dermatòlegs per a propòsits relacionats amb la investigació. L’ objectiu principal d’ aquest projecte és desenvolupar un sistema informàtic que proporcioni als dermatòlegs agilitat a l’hora de gestionar les dades dels pacients amb les sevesimatges corresponents, ajudar-los en la realització de deteccions dels nevus d’aquestes imatges, i ajudar-los en la comparació d’exploracions (amb les deteccions realitzades)de diferents èpoques d’un mateix pacient
Estudi i implementació d’un mètode de reconstrucció 3D basat en SfM i registre de vistes 3D parcials
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Aquest projecte es basarà en reconstruir una imatge 3D gran a partir d’una seqüència d’imatges 2D capturades per una càmera. Ens centrem en l’estudi de les bases matemàtiques de la visió per computador així com en diferents mètodes emprats en la reconstrucció 3D d’imatges. Per portar a terme aquest estudi s’utilitza la plataforma de desenvolupament MatLab ja que permet tractar operacions matemàtiques, imatges i matrius de gran tamany amb molta senzillesa, rapidesa i eficiència, per aquesta raó s’usa en moltes recerques sobre aquest tema. El projecte aprofundeix en el tema descrit anteriorment estudiant i implementant un mètode que consisteix en aplicar Structure From Motion (SFM) a pocs frames seguits obtinguts d’una seqüència d’imatges 2D per crear una reconstrucció 3D. Quan s’han creat dues reconstruccions 3D consecutives i fent servir un frame com a mínim en comú entre elles, s’aplica un mètode de registre d’estructures 3D, l’Iterative Closest Point (ICP), per crear una reconstrucció 3D més gran a través d’unir les diferents reconstruccions obtingudes a partir de SfM. El mètode consisteix en anar repetint aquestes operacions fins al final dels frames per poder aconseguir una reconstrucció 3D més gran que les petites imatges que s’aconsegueixen a través de SfM. A la Figura 1 es pot veure un esquema del procés que es segueix. Per avaluar el comportament del mètode, utilitzem un conjunt de seqüències sintètiques i un conjunt de seqüències reals obtingudes a partir d’una càmera. L’objectiu final d’aquest projecte és construir una nova toolbox de MatLab amb tots els mètodes per crear reconstruccions 3D grans per tal que sigui possible tractar amb facilitat aquest problema i seguir-lo desenvolupant en un futur
Resumo:
This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.
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This 30-year-old woman presented with clinical symptoms and signs of intracranial hypertension and Parinaud syndrome secondary to ventriculoperitoneal shunt dysfunction. Magnetic resonance (MR) imaging revealed gross triventricular hydrocephalus with a large suprapineal recess due to aqueductal stenosis. Using an endoscopic approach, a ventriculostomy was performed within the floor of the dilated suprapineal recess. Following this procedure the patient experienced alleviation of all her neurological symptoms and signs. Postoperative MR imaging and cerebrospinal fluid flow studies demonstrated a functioning ventriculostomy. The anatomy of the suprapineal recess and its suitability for endoscopic ventriculostomy are discussed.