194 resultados para Signal Processing, Computer-Assisted
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Stress radiographs have been recommended in order to obtain a better objective quantification of abnormal compartment knee motion. This tool has showed to be superior in quantifying a posterior cruciate ligament (PCL) lesion compared to clinical or arthrometer evaluation. Different radiographic techniques have been described in literature to quantify posterior pathological laxity. In this study we evaluated the total amount of posterior displacement (PTD) and side to side difference (SSD), before and after surgical reconstruction of PCL or PCL and posterolateral complex (PLC), using two different stress radiography techniques (Telos stress and kneeling view). Twenty patients were included in this study. We found a statistical significant difference about both total PTD and SSD among the two techniques preoperatively and at follow-up, with greatest values occurring using the kneeling view. Although stress radiographies has been introduced to allow an objective quantification of laxity in ligamentous injured knee, we believe that further studies on a large numbers of subjects are required to define the relationship between PTD values, measured with stress knee radiography, particularly using kneeling view, and ligamentous knee injury, in order to obtain a real useful tool in the decision making process, as well as to evaluate the outcome after ligamentous surgery.
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BACKGROUND AND PURPOSE: The posterior circulation Acute Stroke Prognosis Early CT Score (pc-ASPECTS) quantifies the extent of early ischemic changes in the posterior circulation with a 10-point grading system. We hypothesized that pc-ASPECTS applied to CT angiography source images predicts functional outcome of patients in the Basilar Artery International Cooperation Study (BASICS). METHODS: BASICS was a prospective, observational registry of consecutive patients with acute symptomatic basilar artery occlusion. Functional outcome was assessed at 1 month. We applied pc-ASPECTS to CT angiography source images of patients with CT angiography for confirmation of basilar artery occlusion. We calculated unadjusted and adjusted risk ratios (RRs) of pc-ASPECTS dichotomized at ≥8 versus <8. Primary outcome measure was favorable outcome (modified Rankin Scale scores 0-3). Secondary outcome measures were mortality and functional independence (modified Rankin Scale scores 0-2). RESULTS: Of 158 patients included, 78 patients had a CT angiography source images pc-ASPECTS≥8. Patients with a pc-ASPECTS≥8 more often had a favorable outcome than patients with a pc-ASPECTS<8 (crude RR, 1.7; 95% CI, 0.98-3.0). After adjustment for age, baseline National Institutes of Health Stroke Scale score, and thrombolysis, pc-ASPECTS≥8 was not related to favorable outcome (RR, 1.3; 95% CI, 0.8-2.2), but it was related to reduced mortality (RR, 0.7; 95% CI, 0.5-0.98) and functional independence (RR, 2.0; 95% CI, 1.1-3.8). In post hoc analysis, pc-ASPECTS dichotomized at ≥6 versus <6 predicted a favorable outcome (adjusted RR, 3.1; 95% CI, 1.2-7.5). CONCLUSIONS: pc-ASPECTS on CT angiography source images independently predicted death and functional independence at 1 month in the CT angiography subgroup of patients in the BASICS registry.
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Introduction: Consultations with patients suffering from chronic pain without objective findings represent a challenge fo r family doctors (FDs). A mutual lack of understanding may arise, which threatens the doctor-patient relationship and may lead to dissatisfaction of both patient and doctor and to a breakdown of the therapeutic alliance. Objectives: This study aims to investigate FDs' potential protective practices to preserve the doctor-patient relationship during this type of consultation. Method: In the first step of this qualitative research, I carried out a range of 10 se- mi-structured interviews with FDs to explore their reported practices and repre- sentations during consultations with people suffering from chronic pain without objective findings. The interviews' transcripts were integrally analysed with computer-assisted thematic content analysis (QSR NVivo ® ) to highlight the main themes related to the topic in the participants' talk. Results: At this point of the research, two types of FDs' protective practices can be identified: first the use of complementary sources of knowledge in addition to the medical model to provide explanations to patients, second the collaboration with multidisciplinary teams or support gr oups that allow them to share profes- sional expertise and emotional experiences. Conclusion: The findings could be useful to develop ways to improve the follow- up of patients suffering from chronic pain without objective findings and conse- quently the FDs' work satisfaction.
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PURPOSE: To assess the diagnostic performance of respiratory self-navigation for whole-heart coronary magnetic resonance (MR) angiography in a patient cohort referred for diagnostic cardiac MR imaging. MATERIALS AND METHODS: Written informed consent was obtained from all participants for this institutional review board-approved study. Self-navigated coronary MR angiography was performed after administration of a contrast agent in 78 patients (mean age, 48.5 years ± 20.7 [standard deviation]; 53 male patients) referred for cardiac MR imaging because of coronary artery disease (n = 40), cardiomyopathy (n = 14), congenital anomaly (n = 17), or "other" (n = 7). Examination duration was recorded, and the image quality for each coronary segment was assessed with consensus reading. Vessel sharpness, length, and diameter were measured. Quantitative values in proximal, middle, and distal segments were compared by using analysis of variance and t tests. A double-blinded comparison with the results of x-ray angiography was performed when such results were available. RESULTS: When patients with different indications for cardiac MR imaging were examined with self-navigated postcontrast coronary MR angiography, whole-heart data sets with 1.15-mm isotropic spatial resolution were acquired in an average of 7.38 minutes ± 1.85. The main and proximal coronary segments could be visualized in 92.3% of cases, while the middle and distal segments could be visualized in 84.0% and 55.8% of cases, respectively. Subjective scores and vessel sharpness were significantly higher in the proximal segments than in the middle and distal segments (P < .05). Anomalies of the coronary arteries could be confirmed or excluded in all cases. Per-vessel sensitivity and specificity for stenosis detection were 64.7% and 85.0%, respectively, in the 31 patients for whom reference standard x-ray coronary angiography results were available. CONCLUSION: The self-navigated coronary MR angiography sequence shows promise for coronary imaging. However, technical improvements are needed to improve image quality, especially in the more distal coronary segments.
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An objective analysis of image quality parameters was performed for a computed radiography (CR) system using both standard single-side and prototype dual-side read plates. The pre-sampled modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) for the systems were determined at three different beam qualities representative of pediatric chest radiography, at an entrance detector air kerma of 5 microGy. The NPS and DQE measurements were realized under clinically relevant x-ray spectra for pediatric radiology, including x-ray scatter radiations. Compared to the standard single-side read system, the MTF for the dual-side read system is reduced, but this is offset by a significant decrease in image noise, resulting in a marked increase in DQE (+40%) in the low spatial frequency range. Thus, for the same image quality, the new technology permits the CR system to be used at a reduced dose level.
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Given the significant impact the use of glucocorticoids can have on fracture risk independent of bone density, their use has been incorporated as one of the clinical risk factors for calculating the 10-year fracture risk in the World Health Organization's Fracture Risk Assessment Tool (FRAX(®)). Like the other clinical risk factors, the use of glucocorticoids is included as a dichotomous variable with use of steroids defined as past or present exposure of 3 months or more of use of a daily dose of 5 mg or more of prednisolone or equivalent. The purpose of this report is to give clinicians guidance on adjustments which should be made to the 10-year risk based on the dose, duration of use and mode of delivery of glucocorticoids preparations. A subcommittee of the International Society for Clinical Densitometry and International Osteoporosis Foundation joint Position Development Conference presented its findings to an expert panel and the following recommendations were selected. 1) There is a dose relationship between glucocorticoid use of greater than 3 months and fracture risk. The average dose exposure captured within FRAX(®) is likely to be a prednisone dose of 2.5-7.5 mg/day or its equivalent. Fracture probability is under-estimated when prednisone dose is greater than 7.5 mg/day and is over-estimated when the prednisone dose is less than 2.5 mg/day. 2) Frequent intermittent use of higher doses of glucocorticoids increases fracture risk. Because of the variability in dose and dosing schedule, quantification of this risk is not possible. 3) High dose inhaled glucocorticoids may be a risk factor for fracture. FRAX(®) may underestimate fracture probability in users of high dose inhaled glucocorticoids. 4) Appropriate glucocorticoid replacement in individuals with adrenal insufficiency has not been found to increase fracture risk. In such patients, use of glucocorticoids should not be included in FRAX(®) calculations.
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With increasing costs for conducting surveys, many survey agencies resort to implementing call strategies. Obtaining contact in panel surveys as early as possible, without annoying people by contacting them at undesired times and ultimately causing them to refuse, requires using efficient call time strategies. In this research, the author uses call data from the Swiss Household Panel (SHP), a centralized Computer Assisted Telephone Interview (CATI) survey with a randomized (experimental) call-household assignment. Using random effects models, the author analyzes the efficiency gains of obtaining initial contact by assigning optimal times to first calls, and times and spacing to second and later calls depending on household sociodemography and prior call patterns. The author concludes with some recommendations for making early and successful contact during fieldwork.
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A fully-automated 3D image analysis method is proposed to segment lung nodules in HRCT. A specific gray-level mathematical morphology operator, the SMDC-connection cost, acting in the 3D space of the thorax volume is defined in order to discriminate lung nodules from other dense (vascular) structures. Applied to clinical data concerning patients with pulmonary carcinoma, the proposed method detects isolated, juxtavascular and peripheral nodules with sizes ranging from 2 to 20 mm diameter. The segmentation accuracy was objectively evaluated on real and simulated nodules. The method showed a sensitivity and a specificity ranging from 85% to 97% and from 90% to 98%, respectively.
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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).
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In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.
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In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.
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In order to understand relationships between executive and structural deficits in the frontal cortex of patients within normal aging or Alzheimer's disease, we studied frontal pathological changes in young and old controls compared to cases with sporadic (AD) or familial Alzheimer's disease (FAD). We performed a semi-automatic computer assisted analysis of the distribution of beta-amyloid (Abeta) deposits revealed by Abeta immunostaining as well as of neurofibrillary tangles (NFT) revealed by Gallyas silver staining in Brodman areas 10 (frontal polar), 12 (ventro-infero-median) and 24 (anterior cingular), using tissue samples from 5 FAD, 6 sporadic AD and 10 control brains. We also performed densitometric measurements of glial fibrillary acidic protein, principal compound of intermediate filaments of astrocytes, and of phosphorylated neurofilament H and M epitopes in areas 10 and 24. All regions studied seem almost completely spared in normal old controls, with only the oldest ones exhibiting a weak percentage of beta-amyloid deposit and hardly any NFT. On the contrary, all AD and FAD cases were severely damaged as shown by statistically significant increased percentages of beta-amyloid deposit, as well as by a high number of NFT. FAD cases (all from the same family) had statistically more beta-amyloid and GFAP than sporadic AD cases in both areas 10 and 24 and statistically more NFT only in area 24. The correlation between the percentage of beta-amyloid and the number of NFT was significant only for area 24. Altogether, these data suggest that the frontal cortex can be spared by AD type lesions in normal aging, but is severely damaged in sporadic and still more in familial Alzheimer's disease. The frontal regions appear to be differentially vulnerable, with area 12 having the less amyloid burden, area 24 the less NFT and area 10 having both more amyloid and more NFT. This pattern of damage in frontal regions may represent a strong neuroanatomical support for the deterioration of attention and cognitive capacities as well as for the presence of emotional and behavioral troubles in AD patients.
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A new ambulatory method of monitoring physical activities in Parkinson's disease (PD) patients is proposed based on a portable data-logger with three body-fixed inertial sensors. A group of ten PD patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) and ten normal control subjects followed a protocol of typical daily activities and the whole period of the measurement was recorded by video. Walking periods were recognized using two sensors on shanks and lying periods were detected using a sensor on trunk. By calculating kinematics features of the trunk movements during the transitions between sitting and standing postures and using a statistical classifier, sit-to-stand (SiSt) and stand-to-sit (StSi) transitions were detected and separated from other body movements. Finally, a fuzzy classifier used this information to detect periods of sitting and standing. The proposed method showed a high sensitivity and specificity for the detection of basic body postures allocations: sitting, standing, lying, and walking periods, both in PD patients and healthy subjects. We found significant differences in parameters related to SiSt and StSi transitions between PD patients and controls and also between PD patients with and without STN-DBS turned on. We concluded that our method provides a simple, accurate, and effective means to objectively quantify physical activities in both normal and PD patients and may prove useful to assess the level of motor functions in the latter.
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We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.