RESUMO
Two semi-automatic methods for the detection of the left ventricular border in two-dimensional short axis echocardiographic images are presented and compared. In these methods, the left ventricular area variation curve is calculated during a complete cardiac cycle after the segmentation of several frames. This allows the evaluation of the cardiovascular dynamics and the identification of important clinical parameters. The algorithms are proposed as several independent modules. The results are validated through the comparison between the semi-automatic continuous boundaries and manuals boundaries sketched by a medical specialist.
Assuntos
Inteligência Artificial , Ecocardiografia/métodos , Ventrículos do Coração/diagnóstico por imagem , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Reconhecimento Automatizado de Padrão/métodos , Técnica de Subtração , Algoritmos , Humanos , Aumento da Imagem/métodos , Reprodutibilidade dos Testes , Sensibilidade e EspecificidadeRESUMO
A new left ventricle segmentation method in two-dimensional echocardiography images is proposed. Image processing techniques combined with radial search and temporal information are used to extract the left ventricle boundary. Borders from sequential images are extracted using the proposed method, and a curve illustrating the area variation within a cardiac cycle is presented. Performance evaluation is performed by comparing the borders obtained from the presented method to those manually prescribed by a medical specialist. The new sequential radial search algorithm improved the border extraction from long-axis ultrasound images, specially the ones where the mitral valve was open. Segmentation errors due to low contrast were corrected.
