996 resultados para product image


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OBJECTIVE. The purpose of the study was to investigate patient characteristics associated with image quality and their impact on the diagnostic accuracy of MDCT for the detection of coronary artery stenosis. MATERIALS AND METHODS. Two hundred ninety-one patients with a coronary artery calcification (CAC) score of <= 600 Agatston units (214 men and 77 women; mean age, 59.3 +/- 10.0 years [SD]) were analyzed. An overall image quality score was derived using an ordinal scale. The accuracy of quantitative MDCT to detect significant (>= 50%) stenoses was assessed using quantitative coronary angiography (QCA) per patient and per vessel using a modified 19-segment model. The effect of CAC, obesity, heart rate, and heart rate variability on image quality and accuracy were evaluated by multiple logistic regression. Image quality and accuracy were further analyzed in subgroups of significant predictor variables. Diagnostic analysis was determined for image quality strata using receiver operating characteristic (ROC) curves. RESULTS. Increasing body mass index (BMI) (odds ratio [OR] = 0.89, p < 0.001), increasing heart rate (OR = 0.90, p < 0.001), and the presence of breathing artifact (OR = 4.97, p = 0.001) were associated with poorer image quality whereas sex, CAC score, and heart rate variability were not. Compared with examinations of white patients, studies of black patients had significantly poorer image quality (OR = 0.58, p = 0.04). At a vessel level, CAC score (10 Agatston units) (OR = 1.03, p = 0.012) and patient age (OR = 1.02, p = 0.04) were significantly associated with the diagnostic accuracy of quantitative MDCT compared with QCA. A trend was observed in differences in the areas under the ROC curves across image quality strata at the vessel level (p = 0.08). CONCLUSION. Image quality is significantly associated with patient ethnicity, BMI, mean scan heart rate, and the presence of breathing artifact but not with CAC score at a patient level. At a vessel level, CAC score and age were associated with reduced diagnostic accuracy.

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In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

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Objectives To evaluate the gene expression profile of fibroblasts from affected and non-affected skin of systemic sclerosis (SSc) patients and from controls. Materials and methods Labeled cDNA from fibroblast cultures from forearm (affected) and axillary (non-affected) skin from six diffuse SSc patients, from three normal controls, and from MOLT-4/HEp-2/normal fibroblasts (reference pool) was probed in microarrays generated with 4193 human cDNAs from the IMAGE Consortium. Microarray images were converted into numerical data and gene expression was calculated as the ratio between fibroblast cDNA (Cy5) and reference pool cDNA (Cy3) data and analyzed by R environment/Aroma, Cluster, Tree View, and SAM softwares. Differential expression was confirmed by real time PCR for a set of selected genes. Results Eighty-eight genes were up- and 241 genes down-regulated in SSc fibroblasts. Gene expression correlation was strong between affected and non-affected fibroblast samples from the same patient (r>0.8), moderate among fibroblasts from all patients (r=0.72) and among fibroblasts from all controls (r=0.70), and modest among fibroblasts from patients and controls (r=0.55). The differential expression was confirmed by real time PCR for all selected genes. Conclusions Fibroblasts from affected and non-affected skin of SSc patients shared a similar abnormal gene expression profile, suggesting that the widespread molecular disturbance in SSc fibroblasts is more sensitive than histological and clinical alterations. Novel molecular elements potentially involved in SSc pathogenesis were identified.

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In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

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Background: Some ovarian metaplasias may contain bone or osteoid tissue. The most common tumors presenting these alterations are teratomas and mixed mesodermal tumors with heterologous elements. Case report: We report the case of a woman who, during gynecologic follow-up for chronic anovulation at the age of 31 years, presented a solid ovarian ultrasonographic image with calcifications. After laparoscopy and histological examination it was found to be an isolated ovarian osseous metaplasia. Conclusion: A rarely occurring condition, ovarian osseous metaplasia continues to be of uncertain clinical significance.

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Functional brain imaging techniques such as functional MRI (fMRI) that allow the in vivo investigation of the human brain have been exponentially employed to address the neurophysiological substrates of emotional processing. Despite the growing number of fMRI studies in the field, when taken separately these individual imaging studies demonstrate contrasting findings and variable pictures, and are unable to definitively characterize the neural networks underlying each specific emotional condition. Different imaging packages, as well as the statistical approaches for image processing and analysis, probably have a detrimental role by increasing the heterogeneity of findings. In particular, it is unclear to what extent the observed neurofunctional response of the brain cortex during emotional processing depends on the fMRI package used in the analysis. In this pilot study, we performed a double analysis of an fMRI dataset using emotional faces. The Statistical Parametric Mapping (SPM) version 2.6 (Wellcome Department of Cognitive Neurology, London, UK) and the XBAM 3.4 (Brain Imaging Analysis Unit, Institute of Psychiatry, Kings College London, UK) programs, which use parametric and non-parametric analysis, respectively, were used to assess our results. Both packages revealed that processing of emotional faces was associated with an increased activation in the brain`s visual areas (occipital, fusiform and lingual gyri), in the cerebellum, in the parietal cortex, in the cingulate cortex (anterior and posterior cingulate), and in the dorsolateral and ventrolateral prefrontal cortex. However, blood oxygenation level-dependent (BOLD) response in the temporal regions, insula and putamen was evident in the XBAM analysis but not in the SPM analysis. Overall, SPM and XBAM analyses revealed comparable whole-group brain responses. Further Studies are needed to explore the between-group compatibility of the different imaging packages in other cognitive and emotional processing domains. (C) 2009 Elsevier Ltd. All rights reserved.

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Introduction. In view of the high prevalence of headache in the general population, the availability of well defined regarding the request of complementary exams is highly desirable. Aim. To analyze the criteria that will guide the physician requests of complementary exams during the investigation of headache. Patients and methods. The data were obtained by reviewing medical records of all patients who had been scheduled to be seen in a tertiary Headache Outpatient Clinic in 2004. Results. The exam most frequently requested was computed tomography of the head and the exams that most contributed to a change in clinical diagnosis or medical conduct were computed tomography of paranasal sinuses, simple rediography of paranasal sinuses. and magnetic resonance image of the brain. The exams that did not contribute to a change in the diagnosis or medical conduct were computed tomography and simple radiography of the cervical spine. As expected, the most expensive exams for the institution were computed tomography and magnetic resonance image. Conclusion. The importance of complementary exams in the investigation of headache is indisputable in many cases. Howerer, it is necessary the availability of more, studies that evaluate the request of complementay ; exams for headache patients. [REV NEUROL 2009: 48: 183-7]

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There is virtually no literature on the effect of correction of syndromal faciocraniosynostosis with monobloc advancement on the palpebral fissure shape. Using image processing software, we measured the effect of monobloc advancement on the position of the upper and lower eyelids as well as the palpebral fissure slant in a series of 18 patients with syndromal faciocraniosynostosis who had undergone surgery for correction of orbital and midface hypoplasia. For both eyed of each patient, 3 variables were measured on the pre- and postoperative photographs: the linear distances between the upper and lower eyelid margins, the pupil center and the angle between the inner and outer canthi. The globe protrusion was also measured on axial computed tomography scans before and after surgery. The results indicate that the exorbitism reduction induced by monobloc advancement is accompanied by a diminution of the distance between both eyelids and the pupil center. However, the downward slant of the palpebral fissure is increased after surgery. The data suggest that the lower and upper eyelid retraction seen preoperatively in the majority of patients with faciocraniosynostosis tend to be corrected when the frontofacial region is advanced by the monobloc. On the other hand, the surgery tends to lower the outer canthus, increasing the negative slant of the fissure. The postoperative changes induced by the frontofacial monobloc advancement need to be taken into account when the surgery is going to be performed.

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Osteoarthritis (OA) is a widely prevalent disease of the whole joint including cartilage, bone and soft tissues. Increasing importance of imaging including assessment of all joint structures has been recognized recently. Conventional radiography is still the first and most commonly used imaging technique for evaluation of a patient with a known or suspected diagnosis of OA. However, limitations have been revealed by recent MRI-based knee OA studies. MRI plays a crucial role in understanding the natural history of the disease and in guiding future therapies due to its ability to image the knee as a whole organ and to directly and three-dimensionally assess cartilage morphology and composition. It is crucial to use the appropriate MR pulse sequences to assess various OA features, and thus support from experienced musculoskeletal radiologists should be sought for study design, image acquisition and interpretation. The aim of this article is to describe the roles and limitations of conventional radiography and MRI in imaging of OA, and also to give insight into the use of other modalities such as ultrasound, scintigraphy, computed tomography (CT) and CT arthrography in clinical practice and research in OA, particularly focusing on the assessment of knee OA in the tibiofemoral joint.