DETECTION OF MASSES IN MAMMOGRAPHY IMAGES USING CELLULAR NEURAL NETWORKS, STATISCAL FUNCTIONS VECTOR MACHINES AND SUPPORT / DETECÇÃO DE MASSAS EM IMAGENS MAMOGRÁFICAS USANDO REDES NEURAIS CELULARES, FUNÇÕES GEOESTATÍSTICAS E MÁQUINAS DE VETORES DE SUPORTE
AUTOR(ES)
WENER BORGES DE SAMPAIO
DATA DE PUBLICAÇÃO
2009
RESUMO
Breast cancer presents high occurrence frequency among the world population and its psychological effects alter the perception of the patients sexuality and the own personal image. Mammography is an x-ray of the mamma that allows the precocious detection of cancer, since it is capable to showing lesions in their initial stages, typically very small lesions in the order of millimeters. The processing of mammographic images has been contributing to the detection and the diagnosis of mammary nodules, being an important tool, because it reduces the degree of uncertainty of the diagnosis, providing a supplementary source of information to the specialist. This work presents a computational methodology that aids the specialist in the detection of breast masses. The first step of the methodology aims at improvement the mammographic image, which consists of removal of unwanted objects, reduction of noise and enhancement of the breast internal structures. Then, Cellular Neural Networks are used to segment areas suspected of containing masses. These regions have their shapes analyzed by geometry descriptors (eccentricity, circularity, compactness, circular disproportion and circular density) and their textures are analyzed using geostatistical functions (Ripley s K function, Moran s and Geary s indices). Support Vector Machine were trained and used to classify the candidate regions in one of the classes, masses or no-mass, with sensibility of 80.00%, specificity of 85.68%, acuracy of 84.62%, a rate of 0.84 false positive for image and 0.20 false negative for image and an area under the curve ROC of 0.827.
ASSUNTO(S)
support vector machine mammography Índice de moran coeficiente de geary detecção auxiliada por computador cellular neural networks mamografia engenharia biomedica gearys index morans index redes celulares neurais máquina de vetores de suporte função k de ripley ripleys k function computer-aided detection
ACESSO AO ARTIGO
http://www.tedebc.ufma.br//tde_busca/arquivo.php?codArquivo=356Documentos Relacionados
- Breast tumor classification in ultrasound images using support vector machines and neural networks
- Comite de maquinas : uma abordagem unificada empregando maquinas de vetores-suporte
- Detecção de falhas em motores elétricos através das máquinas de vetores de suporte
- CLASSIFICAÇÃO DE MASSAS NA MAMA A PARTIR DE IMAGENS MAMOGRÁFICAS USANDO ÍNDICE DE DIVERSIDADE DE SHANNON-WIENER
- Detecção de bordas em imagens de ecocardiografia utilizando redes neurais artificiais.