Simulador radiográfico antropomórfico de mama humana

Mammography is a diagnostic imaging method in which interpretation depends on knowledge of radiological aspects as well as the clinical exam and pathophysiology of breast diseases. In this work a mammography phantom was developed to be used for training in the operation of mammographic x-ray equipment, image quality evaluation, self-examination and clinical examination of palpation. Polyurethane was used for the production of the phantoms for its physical and chemical properties and because it is one of the components normally used in prostheses. According to the range of flexibility of the polyurethane, it was possible to simulate breasts with higher or lower amount of adipose tissue. Pathologies such as areolar necrosis and tissue rejection due to surgery reconstruction after partial mastectomy were also simulated. Calcifications and nodules were simulated using the following materials: polyethylene, poly (methyl methacrylate), polyamide, polyurethane and poly (dimethyl silicone). Among these, polyethylene was able to simulate characteristics of calcification as well as breast nodules. The results from mammographic techniques used in this paper for the evaluation of the phantoms are in agreement with data found in the literature. The image analyses of four phantoms indicated significant similarities with the human skin texture and the female breast parenchyma. It was possible to detect in the radiographic images produced regions of high and low radiographic optical density, which are characteristic of breasts with regions of different amount of adipose tissue. The stiffnesses of breast phantoms were adjusted according to the formulation of the polyurethane which enabled the production of phantoms with distinct radiographic features and texture similar to human female breast parenchyma. Clinical palpation exam of the phantoms developed in this work indicated characteristics similar to human breast in skin texture, areolar region and parenchyma

Abordagem inicial de lesões mamárias por biopsia helicóide: estudo experimental

OBJECTIVE: Evaluating the kit-Bh performance in carrying out of breast biopsies. METHODS: They were randomly selected a sample of 30 patients with breast cancer undergoing mastectomy, based on the results of a pilot study from February 2008 to April 2010. They were excluded women with had not palpable, stone-hard consistency tumors, previous surgical manipulation or that contains liquid. Using the helicoid biopsy Kit (kit Bh) and an equipment Core biopsy with cannula and needle and 14 gauge respectively, it was collected a fragment of sound equipment in the area and in tumors in each specimen, totaling 120 fragments for histological study. For data analysis, it was defined a 95% confidence level and used the SPSS-13 version, the Kappa index and the parametric Student t test. RESULTS: Mean age of patients was 51.6 years (± 11.1 years). The infiltrating ductal carcinoma showed a higher incidence, 26 cases (86.7%). The Core biopsy had a sensitivity of 93.3%, specificity of 100% and accuracy 96.7%, while the helicoid biopsy had a sensitivity of 96.7%, specificity of 100% and accuracy 98.3%. By comparing the histology of tumors and the fragments of biopsies, there was high degree of agreement in diagnoses (kappa of 0.93 with p <0.05) CONCLUSION: Both devices provided the histological diagnosis of lesions with high accuracy. Results of this study showed that the helicoid biopsy is a reliable alternative in 22 the preoperative diagnosis of breast lesions. Further studies in vivo better will define the role of Kit Bh in the diagnosis of these lesions

Trajetória de vida de mulheres mastectomizadas integrantes de um grupo de auto ajuda a luz da História Oral

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Segmentação Fuzzy de Texturas e Vídeos

The segmentation of an image aims to subdivide it into constituent regions or objects that have some relevant semantic content. This subdivision can also be applied to videos. However, in these cases, the objects appear in various frames that compose the videos. The task of segmenting an image becomes more complex when they are composed of objects that are defined by textural features, where the color information alone is not a good descriptor of the image. Fuzzy Segmentation is a region-growing segmentation algorithm that uses affinity functions in order to assign to each element in an image a grade of membership for each object (between 0 and 1). This work presents a modification of the Fuzzy Segmentation algorithm, for the purpose of improving the temporal and spatial complexity. The algorithm was adapted to segmenting color videos, treating them as 3D volume. In order to perform segmentation in videos, conventional color model or a hybrid model obtained by a method for choosing the best channels were used. The Fuzzy Segmentation algorithm was also applied to texture segmentation by using adaptive affinity functions defined for each object texture. Two types of affinity functions were used, one defined using the normal (or Gaussian) probability distribution and the other using the Skew Divergence. This latter, a Kullback-Leibler Divergence variation, is a measure of the difference between two probability distributions. Finally, the algorithm was tested in somes videos and also in texture mosaic images composed by images of the Brodatz album

Segmentação fuzzy de imagens e vídeos

Image segmentation is the process of subdiving an image into constituent regions or objects that have similar features. In video segmentation, more than subdividing the frames in object that have similar features, there is a consistency requirement among segmentations of successive frames of the video. Fuzzy segmentation is a region growing technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership between 0 and 1 to an object. In this work we present an application that uses a fuzzy segmentation algorithm to identify and select particles in micrographs and an extension of the algorithm to perform video segmentation. Here, we treat a video shot is treated as a three-dimensional volume with different z slices being occupied by different frames of the video shot. The volume is interactively segmented based on selected seed elements, that will determine the affinity functions based on their motion and color properties. The color information can be extracted from a specific color space or from three channels of a set of color models that are selected based on the correlation of the information from all channels. The motion information is provided into the form of dense optical flows maps. Finally, segmentation of real and synthetic videos and their application in a non-photorealistic rendering (NPR) toll are presented

Segmentação fuzzy de objetos tridimensionais com propriedades texturais

Digital image segmentation is the process of assigning distinct labels to different objects in a digital image, and the fuzzy segmentation algorithm has been used successfully in the segmentation of images from several modalities. However, the traditional fuzzy segmentation algorithm fails to segment objects that are characterized by textures whose patterns cannot be successfully described by simple statistics computed over a very restricted area. In this paper we present an extension of the fuzzy segmentation algorithm that achieves the segmentation of textures by employing adaptive affinity functions as long as we extend the algorithm to tridimensional images. The adaptive affinity functions change the size of the area where they compute the texture descriptors, according to the characteristics of the texture being processed, while three dimensional images can be described as a finite set of two-dimensional images. The algorithm then segments the volume image with an appropriate calculation area for each texture, making it possible to produce good estimates of actual volumes of the target structures of the segmentation process. We will perform experiments with synthetic and real data in applications such as segmentation of medical imaging obtained from magnetic rosonance

Doença de Chagas: caracterização de formas clínicas e estratificação do risco de morte no Oeste do Estado do Rio Grande do Norte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES

Avaliação da imagem corporal de mulheres submetidas à cirurgia oncológica mamária

Breast cancer is the second type of cancer that affects more women of reproductive age in Brazil. Surgical treatments include: conserving surgery or mastectomy. Aimed to evaluate body image of women undergoing breast cancer surgery, based on the scale Body Image After Breast Cancer Questionnaire. It is a descriptive, exploratory, transversal, with a quantitative approach. Data were collected in Norte-riograndense League Against Cancer, between the months from March to May 2015, after consideration of the Research Ethics Committee of that institution CAEE 35155714.1.0000.5293. The study population consisted of women undergoing breast onco-surgery. To calculate the sample considered the finite population, totaling 120 subjects, collected four guys the most. Data were analyzed by the software Statistical Package for Social Sciences version 20.0. The domain scores of the scale were evaluated using descriptive and inferential statistics. The surgical group mastectomy without reconstruction showed greater impairment of body image in the field "vulnerability", "Care for the body" and "transparency" in relation to other surgical types, and suggests susceptibility to cancer, body appearance and worry that disturb other. The Kruskal-Wallis test showed greater dissatisfaction with body image in the fields "body Stigma" and "transparency" to the radical neoplastic surgery over other surgical types. Dissatisfaction with body image and physical appearance was detected in this study in all six image fields present in scale, with emphasis on the "body Stigma" and "Transparency". This means that the body image disorder is formulated based on the perception of others about themselves and not by perception "self", which justifies the concern with appearance, with body and hide the consequences stemmed cancer. It is expected that the data obtained from the evaluation of body image presented in this study contribute to enable the assistance to oncocirurgiada woman breast integral, essential for the practice of Nursing.

Avaliação da imagem corporal de mulheres submetidas à cirurgia oncológica mamária

Breast cancer is the second type of cancer that affects more women of reproductive age in Brazil. Surgical treatments include: conserving surgery or mastectomy. Aimed to evaluate body image of women undergoing breast cancer surgery, based on the scale Body Image After Breast Cancer Questionnaire. It is a descriptive, exploratory, transversal, with a quantitative approach. Data were collected in Norte-riograndense League Against Cancer, between the months from March to May 2015, after consideration of the Research Ethics Committee of that institution CAEE 35155714.1.0000.5293. The study population consisted of women undergoing breast onco-surgery. To calculate the sample considered the finite population, totaling 120 subjects, collected four guys the most. Data were analyzed by the software Statistical Package for Social Sciences version 20.0. The domain scores of the scale were evaluated using descriptive and inferential statistics. The surgical group mastectomy without reconstruction showed greater impairment of body image in the field "vulnerability", "Care for the body" and "transparency" in relation to other surgical types, and suggests susceptibility to cancer, body appearance and worry that disturb other. The Kruskal-Wallis test showed greater dissatisfaction with body image in the fields "body Stigma" and "transparency" to the radical neoplastic surgery over other surgical types. Dissatisfaction with body image and physical appearance was detected in this study in all six image fields present in scale, with emphasis on the "body Stigma" and "Transparency". This means that the body image disorder is formulated based on the perception of others about themselves and not by perception "self", which justifies the concern with appearance, with body and hide the consequences stemmed cancer. It is expected that the data obtained from the evaluation of body image presented in this study contribute to enable the assistance to oncocirurgiada woman breast integral, essential for the practice of Nursing.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Simulador radiográfico antropomórfico de mama humana

Mammography is a diagnostic imaging method in which interpretation depends on knowledge of radiological aspects as well as the clinical exam and pathophysiology of breast diseases. In this work a mammography phantom was developed to be used for training in the operation of mammographic x-ray equipment, image quality evaluation, self-examination and clinical examination of palpation. Polyurethane was used for the production of the phantoms for its physical and chemical properties and because it is one of the components normally used in prostheses. According to the range of flexibility of the polyurethane, it was possible to simulate breasts with higher or lower amount of adipose tissue. Pathologies such as areolar necrosis and tissue rejection due to surgery reconstruction after partial mastectomy were also simulated. Calcifications and nodules were simulated using the following materials: polyethylene, poly (methyl methacrylate), polyamide, polyurethane and poly (dimethyl silicone). Among these, polyethylene was able to simulate characteristics of calcification as well as breast nodules. The results from mammographic techniques used in this paper for the evaluation of the phantoms are in agreement with data found in the literature. The image analyses of four phantoms indicated significant similarities with the human skin texture and the female breast parenchyma. It was possible to detect in the radiographic images produced regions of high and low radiographic optical density, which are characteristic of breasts with regions of different amount of adipose tissue. The stiffnesses of breast phantoms were adjusted according to the formulation of the polyurethane which enabled the production of phantoms with distinct radiographic features and texture similar to human female breast parenchyma. Clinical palpation exam of the phantoms developed in this work indicated characteristics similar to human breast in skin texture, areolar region and parenchyma