210 resultados para Markup Language for Manuscript Images
Resumo:
Purpose: To evaluate the diagnostic value and image quality of CT with filtered back projection (FBP) compared with adaptive statistical iterative reconstructed images (ASIR) in body stuffers with ingested cocaine-filled packets.Methods and Materials: Twenty-nine body stuffers (mean age 31.9 years, 3 women) suspected for ingestion of cocaine-filled packets underwent routine-dose 64-row multidetector CT with FBP (120kV, pitch 1.375, 100-300 mA and automatic tube current modulation (auto mA), rotation time 0.7sec, collimation 2.5mm), secondarily reconstructed with 30 % and 60 % ASIR. In 13 (44.83%) out of the body stuffers cocaine-filled packets were detected, confirmed by exact analysis of the faecal content including verification of the number (range 1-25). Three radiologists independently and blindly evaluated anonymous CT examinations (29 FBP-CT and 68 ASIR-CT) for the presence and number of cocaine-filled packets indicating observers' confidence, and graded them for diagnostic quality, image noise, and sharpness. Sensitivity, specificity, area under the receiver operating curve (ROC) Az and interobserver agreement between the 3 radiologists for FBP-CT and ASIR-CT were calculated.Results: The increase of the percentage of ASIR significantly diminished the objective image noise (p<0.001). Overall sensitivity and specificity for the detection of the cocaine-filled packets were 87.72% and 76.15%, respectively. The difference of ROC area Az between the different reconstruction techniques was significant (p= 0.0101), that is 0.938 for FBP-CT, 0.916 for 30 % ASIR-CT, and 0.894 for 60 % ASIR-CT.Conclusion: Despite the evident image noise reduction obtained by ASIR, the diagnostic value for detecting cocaine-filled packets decreases, depending on the applied ASIR percentage.
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In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.
Resumo:
Language is typically a function of the left hemisphere but the right hemisphere is also essential in some healthy individuals and patients. This inter-subject variability necessitates the localization of language function, at the individual level, prior to neurosurgical intervention. Such assessments are typically made by comparing left and right hemisphere language function to determine "language lateralization" using clinical tests or fMRI. Here, we show that language function needs to be assessed at the region and hemisphere specific level, because laterality measures can be misleading. Using fMRI data from 82 healthy participants, we investigated the degree to which activation for a semantic word matching task was lateralized in 50 different brain regions and across the entire cortex. This revealed two novel findings. First, the degree to which language is lateralized across brain regions and between subjects was primarily driven by differences in right hemisphere activation rather than differences in left hemisphere activation. Second, we found that healthy subjects who have relatively high left lateralization in the angular gyrus also have relatively low left lateralization in the ventral precentral gyrus. These findings illustrate spatial heterogeneity in language lateralization that is lost when global laterality measures are considered. It is likely that the complex spatial variability we observed in healthy controls is more exaggerated in patients with brain damage. We therefore highlight the importance of investigating within hemisphere regional variations in fMRI activation, prior to neuro-surgical intervention, to determine how each hemisphere and each region contributes to language processing. Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc.
Resumo:
Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.
Resumo:
OBJECTIVE: To test the ability of a novel phase-shifting medium (PSM) to provide sustained distension of the uterine cavity and produce saline infusion sonography (SIS)-like images in a simplified contrast ultrasound procedure. DESIGN: Prospective pilot feasibility trial of a new diagnostic procedure, contrast ultrasound. SETTING: Clinical reproductive endocrine and infertility unit of regional teaching hospital. PATIENT(S): Twenty-six asymptomatic infertile women (group I) and 27 women presenting with dysfunctional uterine bleeding (DUB) who were scheduled for exploratory surgery (group II). INTERVENTION(S): All women who were temporarily on oral contraceptive first had a regular pelvic ultrasound followed by the intrauterine instillation of up to 3 mL PSM, using a regular insemination catheter, after which all instruments were removed and a regular ultrasound was performed again. RESULT(S): In all 53 women, intrauterine instillation of 1-3 mL PSM resulted in a 3-7 mm uterine distension, sufficient to produce SIS-like images of the uterine cavity that lasted 7-10 min. Contrast ultrasound revealed an endometrial polyp in 3 asymptomatic women of group I. In group II. 12 of 14 women (86%) whose vaginal ultrasound were positive or dubious had positive findings with contrast ultrasound; 9 of 12 patients whose vaginal ultrasounds were negative also had positive contrast ultrasound findings. All the positive and negative findings of contrast ultrasound made in group II were confirmed anatomically (sensitivity and specificity of 100%), whereas the correlation for standard vaginal ultrasound was markedly lower at 57.1% and 85.7%, respectively. Most patients (46 of 53) reported no discomfort during or after the procedure, and 7 women described the procedure as mildly uncomfortable. CONCLUSION(S): Contrast ultrasound, a novel simple diagnostic procedure conducted after intrauterine instillation of 1-3 mL PSM using a simple plastic catheter, delivered SIS-quality images in asymptomatic (group I) and symptomatic (group II) patients while retaining the simplicity of standard ultrasound. We therefore foresee broad application of contrast ultrasound for sensitive and specific assessment for uterine pathologies in the physician's office.
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We present a segmentation method for fetal brain tissuesof T2w MR images, based on the well known ExpectationMaximization Markov Random Field (EM- MRF) scheme. Ourmain contribution is an intensity model composed of 7Gaussian distribution designed to deal with the largeintensity variability of fetal brain tissues. The secondmain contribution is a 3-steps MRF model that introducesboth local spatial and anatomical priors given by acortical distance map. Preliminary results on 4 subjectsare presented and evaluated in comparison to manualsegmentations showing that our methodology cansuccessfully be applied to such data, dealing with largeintensity variability within brain tissues and partialvolume (PV).