999 resultados para archival images


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To compare autofluorescence (AF) images obtained with the confocal scanning laser ophthalmoscope (using the Heidelberg retina angiograph; HRA) and the modified Topcon fundus camera, in a routine clinical setting. A prospective comparative study conducted at the Jules-Gonin Eye Hospital. Fifty-six patients from the medical retina clinic. All patients had complete ophthalmic slit-lamp and fundus examinations, colour and red-free fundus photography, AF imaging with both instruments, and fluorescein angiography. Cataract and fixation were graded clinically. AF patterns were analyzed for healthy and pathological features. Differences of image noise were analyzed by cataract grading and fixation. A total of 105 eyes were included. AF patterns discovered by the retina angiograph and the fundus camera images, respectively, were a dark optic disc in 72 % versus 15 %, a dark fovea in 92 % versus 4 %, sub- and intraretinal fluid visible as hyperautofluorescence on HRA images only, lipid exudates visible as hypoautofluorescence on HRA images only. The same autofluorescent pattern was found on both images for geographic atrophy, retinal pigment changes, drusen and haemorrhage. Image noise was significantly associated with the degree of cataract and/or poor fixation, favouring the fundus camera. Images acquired by the fundus camera before and after fluorescein angiography were identical. Fundus AF images differ according to the technical differences of the instruments used. Knowledge of these differences is important not only for correctly interpreting images, but also for selecting the most appropriate instrument for the clinical situation.

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Background: The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months. Methods: RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score. Results: Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_ 5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_ 5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses. Conclusions: Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer.

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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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Une double démarche est proposée pour appréhender comment des enfants en âge préscolaire élaborent leur compréhension du récit d'un album sans texte, à l'aide d'un adulte dans le contexte d'une Institution de la Petite Enfance (IPE). Si la première analyse porte sur la construction de la compétence narrative et met l'accent sur la nécessité d'un ajustement entre partenaires de l'interaction pour y parvenir, la deuxième se concentre sur les moments de désajustement et leur dépassement, constitutifs eux-aussi de l'apprentissage d'un savoir et de celui de la compétence communicative. Des extraits d'interactions d'une séance de lecture d'images sont analysés pour illustrer ces deux démarches.

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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.