981 resultados para Point pattern matching
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The Pedralta is a loggingstone formed of monzonitic leucogranites, which has a volume of about 38 m3 and weighs 101 tons. After its fall in December 1996, a public subscription was opened to meet the expenses of the restoration work, which was completed in May 1999
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This is the weekly e-Newsletter called “The OCBI Tipping Point.” We hope that you find it very informative as we explore all possibilities to keep our constituency and the general public informed about all matters that affect Blacks in the state of Iowa.
Resumo:
This is the weekly e-Newsletter called “The OCBI Tipping Point.” We hope that you find it very informative as we explore all possibilities to keep our constituency and the general public informed about all matters that affect Blacks in the state of Iowa.
Resumo:
This is the weekly e-Newsletter called “The OCBI Tipping Point.” We hope that you find it very informative as we explore all possibilities to keep our constituency and the general public informed about all matters that affect Blacks in the state of Iowa.
Resumo:
This is the weekly e-Newsletter called “The OCBI Tipping Point.” We hope that you find it very informative as we explore all possibilities to keep our constituency and the general public informed about all matters that affect Blacks in the state of Iowa.
Resumo:
This is the weekly e-Newsletter called “The OCBI Tipping Point.” We hope that you find it very informative as we explore all possibilities to keep our constituency and the general public informed about all matters that affect Blacks in the state of Iowa.
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Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.
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This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results
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This study aims to provide a passive sampling approach which can be routinely used to investigate polychlorinated biphenyl (PCB) sources in rivers. The approach consists of deploying low density polyethylene (LDPE) strips downstream and upstream of potential PCB sources as well as in their water discharges. Concentrations of indicator PCBs (iPCBs) absorbed in samplers (Cs) from upstream and downstream sites are compared with each other to reveal increases of PCB levels. Cs measured in water discharges are used to determine if released amounts of PCBs are compatible with increases revealed in the river. As water velocity can greatly vary along a river stretch and influences the uptake at each site in a different way, differences in velocity have to be taken into account to correctly interpret Cs. LDPE strips were exposed to velocities between 1.6 and 37 cm s−1 using a channel system built in the field. Relationships between velocity and Cs were established for each iPCB to determine the expected change in Cs due to velocity variations. For PCBs 28 and 52, this change does not exceed a factor 2 for velocity variations in the range from 1.6 to 100 cm s−1 (extrapolated data above 37 cm s−1). For PCBs 101, 138, 153 and 180, this change only exceeds a factor 2 in the case of large velocity variations. The approach was applied in the Swiss river Venoge to first conduct a primary investigation of potential PCB sources and then conduct thorough investigations of two suspected sources.
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We recently described the neuroimaging and clinical findings in 6 children with cerebellar clefts and proposed that they result from disruptive changes following prenatal cerebellar hemorrhage. We now report an additional series of 9 patients analyzing the clinical and neuroimaging findings. The clefts were located in the left cerebellar hemisphere in 5 cases, in the right in 3, and bilaterally in one child who had bilateral cerebellar hemorrhages as a preterm infant at 30 weeks gestation. In one patient born at 24 weeks of gestation a unilateral cerebellar hemorrhage has been found at the age of 4 months. Other findings included disordered alignment of the folia and fissures, an irregular gray/white matter junction, and abnormal arborization of the white matter in all cases. Supratentorial abnormalities were found in 4 cases. All but 2 patients were born at term. We confirm the distinct neuroimaging pattern of cerebellar clefts. Considering the documented fetal cerebellar hemorrhage in our first series, we postulate that cerebellar clefts usually represent residual disruptive changes after a prenatal cerebellar hemorrhage. Exceptionally, as now documented in 2 patients, cerebellar clefts can be found after neonatal cerebellar hemorrhages in preterm infants. The short-term outcome in these children was variable.