Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.

A success in Toxinology translational research in Brazil: Bridging the gap

Basic research is fundamental for discovering potential diagnostic and therapeutic tools, including drugs, vaccines and new diagnostic techniques. On this basis, diagnosis and treatment methods for many diseases have been developed. Presently, discovering new candidate molecules and testing them in animals are relatively easy tasks that require modest resources and responsibility. However, crossing the animal-to-human barrier is still a great challenge that most researchers tend to avoid. Thus, bridging this current gap between clinical and basic research must be encouraged and elucidated in training programmes for health professionals. This project clearly shows the challenges faced by a group of Brazilian researchers who, after discovering a new fibrin sealant through 20 years of painstaking basic work, insisted on having the product applied clinically. The Brazilian government has recently become aware of this challenge and has accordingly defined the product as strategic to the public health of the country. Thus, in addition to financing research and development laboratories, resources were invested in clinical trials and in the development of a virtual platform termed the Virtual System to Support Clinical Research (SAVPC); this platform imparts speed, reliability and visibility to advances in product development, fostering interactions among sponsors, physicians, students and, ultimately, the research subjects themselves. This pioneering project may become a future model for other public institutions in Brazil, principally in overcoming neglected diseases, which unfortunately continue to afflict this tropical country. © 2013 Elsevier Ltd.

Evaluating interaction with websites: Case study of a government website of the Brazilian Ministry of labor and employment

This paper presents a usability evaluation of the MTE (Ministry of Labor e Employment) website in order to measure the effectiveness, efficiency and user satisfaction regarding the website. The participants were 12 users (07 users were female and 05 male). The results indicate that although the education level of all participants and computing experience, many of them have had difficulty in finding information and do not recommend the site. © 2013 Springer-Verlag Berlin Heidelberg.

Desenvolvimento de uma ferramenta computacional de apoio ao ensino de sistemas eletrônicos digitais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Quantificação de fibrose e enfisema em pacientes com paracoccidioidomicose (PCM) pulmonar, através de imagens de tomografia computadorizada de alta resolução (TCAR)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geotecnologias aplicadas à caracterização e mapeamento das alterações da cobertura vegetal intra-urbana e da expansão urbana da cidade de Rio Claro (SP)

Pós-graduação em Geografia - IGCE

Avaliação da adaptação marginal de restaurações cerâmicas inlay após a cimentação

Pós-graduação em Odontologia Restauradora - ICT

Método para extração e caracterização de lesões de pele usando difusão anisotrópica, crescimento de regiões, watersheds e contornos ativos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geotecnologias digitais no ensino médio: avaliação prática de seu potencial

Pós-graduação em Geografia - IGCE

Bioinformática estrutural aplicada ao estudo de proteínas alvo do genoma do Mycobacterium tuberculosis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estudo das características morfométricas de diferentes regiões do intestino delgado e índices zootécnicos em quatro linhagens de frangos de corte

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Biophysical and Structural Characterization of the Recombinant Human eIF3L

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Antimalarial activity of piperidine alkaloids from Senna spectabilis and semisynthetic derivatives

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of a CAD system for automatic classification of microcalcifications based on FPGA

This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

Optimum-Path Forest Applied for Breast Masses Classification

In Computer-Aided Diagnosis-based schemes in mammography analysis each module is interconnected, which directly affects the system operation as a whole. The identification of mammograms with and without masses is highly needed to reduce the false positive rates regarding the automatic selection of regions of interest for further image segmentation. This study aims to evaluate the performance of three techniques in classifying regions of interest as containing masses or without masses (without clinical findings), as well as the main contribution of this work is to introduce the Optimum-Path Forest (OPF) classifier in this context, which has never been done so far. Thus, we have compared OPF against with two sorts of neural networks in a private dataset composed by 120 images: Radial Basis Function and Multilayer Perceptron (MLP). Texture features have been used for such purpose, and the experiments have demonstrated that MLP networks have been slightly better than OPF, but the former is much faster, which can be a suitable tool for real-time recognition systems.