78 resultados para MAMMOGRAMS


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency subband it's possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm. © 2008 IEEE.

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PURPOSE: The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively. METHODS: All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed. RESULTS: 278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density. CONCLUSION: CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.

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The main goal of this study was to relate physical changes in image quality measured by Modulation Transfer Function (MTF) to diagnostic accuracy.^ One Hundred and Fifty Kodak Min-R screen/film combination conventional craniocaudal mammograms obtained with the Pfizer Microfocus Mammographic system were selected from the files of the Department of Radiology, at M.D. Anderson Hospital and Tumor Institute.^ The mammograms included 88 cases with a variety of benign diagnosis and 62 cases with a variety of malignant biopsy diagnosis. The average age of the patient population was 55 years old. 70 cases presented calcifications with 30 cases having calcifications smaller than 0.5mm. 46 cases presented irregular bordered masses larger than 1 cm. 30 cases presented smooth bordered masses with 20 larger than 1 cm.^ Four separated copies of the original images were made each having a different change in the MTF using a defocusing technique whereby copies of the original were obtained by light exposure through different thicknesses (spacing) of transparent film base.^ The mammograms were randomized, and evaluated by three experienced mammographers for the degree of visibility of various anatomical breast structures and pathological lesions (masses and calicifications), subjective image quality, and mammographic interpretation.^ 3,000 separate evaluations were anayzed by several statistical techniques including Receiver Operating Characteristic curve analysis, McNemar test for differences between proportions and the Landis et al. method of agreement weighted kappa for ordinal categorical data.^ Results from the statistical analysis show: (1) There were no statistical significant differences in the diagnostic accuracy of the observers when diagnosing from mammograms with the same MTF. (2) There were no statistically significant differences in diagnostic accuracy for each observer when diagnosing from mammograms with the different MTF's used in the study. (3) There statistical significant differences in detail visibility between the copies and the originals. Detail visibility was better in the originals. (4) Feature interpretations were not significantly different between the originals and the copies. (5) Perception of image quality did not affect image interpretation.^ Continuation and improvement of this research ca be accomplished by: using a case population more sensitive to MTF changes, i.e., asymptomatic women with minimum breast cancer, more observers (including less experienced radiologists and experienced technologists) must collaborate in the study, and using a minimum of 200 benign and 200 malignant cases.^

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To analyze associations between mammographic arterial mammary calcifications in menopausal women and risk factors for cardiovascular disease. This was a cross-sectional retrospective study, in which we analyzed the mammograms and medical records of 197 patients treated between 2004 and 2005. Study variables were: breast arterial calcifications, stroke, acute coronary syndrome, age, obesity, diabetes mellitus, smoking, and hypertension. For statistical analysis, we used the Mann-Whitney, χ2 and Cochran-Armitage tests, and also evaluated the prevalence ratios between these variables and mammary artery calcifications. Data were analyzed with the SAS version 9.1 software. In the group of 197 women, there was a prevalence of 36.6% of arterial calcifications on mammograms. Among the risk factors analyzed, the most frequent were hypertension (56.4%), obesity (31.9%), smoking (15.2%), and diabetes (14.7%). Acute coronary syndrome and stroke presented 5.6 and 2.0% of prevalence, respectively. Among the mammograms of women with diabetes, the odds ratio of mammary artery calcifications was 2.1 (95%CI 1.0-4.1), with p-value of 0.02. On the other hand, the mammograms of smokers showed the low occurrence of breast arterial calcification, with an odds ratio of 0.3 (95%CI 0.1-0.8). Hypertension, obesity, diabetes mellitus, stroke and acute coronary syndrome were not significantly associated with breast arterial calcification. The occurrence of breast arterial calcification was associated with diabetes mellitus and was negatively associated with smoking. The presence of calcification was independent of the other risk factors for cardiovascular disease analyzed.

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O objetivo deste estudo é analisar a prevalência da não realização do exame clínico das mamas e da mamografia segundo variáveis sócio-econômicas, demográficas e de comportamentos relacionados à saúde, em mulheres com 40 anos ou mais, residentes na cidade de Campinas, São Paulo, Brasil. O estudo foi do tipo transversal, de base populacional em uma amostra de 290 mulheres. Os fatores associados à não realização da mamografia, encontrados na análise multivariada, foram: ter 70 anos ou mais, ser de raça/cor negra e pertencer ao segmento de menor renda familiar per capita; e para a não realização do exame clínico das mamas foram: não ter companheiro e pertencer ao segmento de menor renda familiar per capita. O SUS foi responsável pela realização de 28,8% das mamografias e 38,2% dos exames clínicos das mamas. Verificou-se que a não realização dos exames preventivos para o câncer de mama está associada à existência de desigualdade racial e social, apontando para a necessidade de implementação de estratégias para a ampliação da cobertura das práticas preventivas para o câncer de mama, especialmente para os segmentos sociais mais vulneráveis.

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We evaluated the performance of a novel procedure for segmenting mammograms and detecting clustered microcalcifications in two types of image sets obtained from digitization of mammograms using either a laser scanner, or a conventional ""optical"" scanner. Specific regions forming the digital mammograms were identified and selected, in which clustered microcalcifications appeared or not. A remarkable increase in image intensity was noticed in the images from the optical scanner compared with the original mammograms. A procedure based on a polynomial correction was developed to compensate the changes in the characteristic curves from the scanners, relative to the curves from the films. The processing scheme was applied to both sets, before and after the polynomial correction. The results indicated clearly the influence of the mammogram digitization on the performance of processing schemes intended to detect microcalcifications. The image processing techniques applied to mammograms digitized by both scanners, without the polynomial intensity correction, resulted in a better sensibility in detecting microcalcifications in the images from the laser scanner. However, when the polynomial correction was applied to the images from the optical scanner, no differences in performance were observed for both types of images. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.3013544]

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This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

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With the increased incidence of cancer and a similarly increased number of surgeries for insertion of silicone breast implants, it is necessary to assess the effect of such material within the breast tissue, particularly in mammography, because of the reduction in the power of breast cancer diagnosis. In this work, we introduce a breast phantom with silicone implants in order to evaluate the influence of the implant on the visibility of the main mammographic findings: fibers, microcalcifications and tumor masses. In this proposed phantom, the breast tissue was simulated using gel paraffin. In the optical density of phantom mammograms with implants, a reduction in breast tissue visibility was seen corresponding to 23% when compared to a phantom without silicone implants. This poor visibility was due to the X-ray beam scattering on silicone material; this effect produced a loss of visibility in the areas adjacent to the implant. It is expected that the proposed phantom model may be used as a device for the establishment of a technical standard for these types of procedures.

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Introduction: Cervical and breast cancer are the most common malignancies among women worldwide. Effective screening can facilitate early detection and dramatically reduce mortality rates. The interface between those screening patients and patients most needing screening is complex, and women in remote areas of rural counties face additional barriers that limit the effectiveness of cancer prevention programs. This study compared various methods to improve compliance with mass screening for breast and cervical cancer among women in a remote, rural region of Brazil. Methods: In 2003, a mobile unit was used to perform 10 156 mammograms and Papanicolaou smear tests for women living in the Barretos County region of Sao Paulo state, Brazil (consisting of 19 neighbouring cities). To reach the women, the following community outreach strategies were used: distribution of flyers and pamphlets; media broadcasts (via radio and car loudspeakers); and community healthcare agents (CHCAs) making home visits. Results: The most useful intervention appeared to be the home visits by healthcare agents or CHCAs. These agents of the Family Health Programme of the Brazilian Ministry of Health reached an average of 45.6% of those screened, with radio advertisements reaching a further 11.9%. The great majority of the screened women were illiterate or had elementary level schooling (80.9%) and were of 'poor' or 'very poor' socioeconomic class (67.2%). Conclusions: Use of a mobile screening unit is a useful strategy in developing countries where local health systems have inadequate facilities for cancer screening in underserved populations. A multimodal approach to community outreach strategies, especially using CHCAs and radio advertisements, can improve the uptake of mass screening in low-income, low-educational background female populations.

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Objectives: To evaluate the effect of a radio and newspaper campaign encouraging Italian-speaking women aged 50-69 years to attend a population-based mammography screening program. Methods: A series of radio scripts and newspaper advertisements ran weekly in the Italian-language media over two, four-week periods. Monthly mammography screens were analysed to determine if numbers of Italian-speaking women in the program increased during the two campaign periods, using interrupted time series regression analysis. A survey of Italian-speaking women attending BreastScreen NSW during the campaign period (n=240) investigated whether individuals had heard or seen the advertisements. Results: There was no statistically significant difference in the number of initial or subsequent mammograms in Italian-speaking women between the campaign periods and the period prior to (or after) the campaign. Twenty per cent of respondents cited the Italian media campaign as a prompt to attend. Fifty per cent had heard the radio ad and 30% had seen the newspaper ad encouraging Italian-speaking women to attend BSNSW. The most common prompt to attend was the BSNSW invitation letter, followed by information or recommendation from a GP. Conclusion: Radio and newspaper advertisements developed for the Italian community did not significantly increase attendance to BSNSW. Implications: Measures of program effectiveness based on self-report may not correspond to aggregate screening behaviour. The development of the media campaign in conjunction with the Italian community, and the provision of appropriate levels of resourcing, did not ensure the media campaign's success.

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This study investigates the relationship between the number of screening mammograms read by radiologists and the screening breast cancer detection rate. Cancer detection rates for incident screens (all women aged >= 40 years) were compared by increasing categories of reader volume using Poisson regression. Data from New South Wales (NSW) for a 2 year period (2000-2001) were obtained from the BreastScreen NSW programme. Cancer detection rates increased with the number of mammograms read in the programme, reaching a plateau of approximately 40 per 10,000 after 1375 mammograms per year. No significant differences in cancer detection were evident above 875 mammograms (compared to below 875 mammograms) per year (RR = 0.79, 95% CI 0.63-0.99). (c) 2005 Elsevier Ltd. All rights reserved.

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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.