Assuntos
Epidemias , Indígenas Norte-Americanos , Poder Psicológico , Varíola , Epidemias/história , História do Século XVIII , Humanos , Indígenas Norte-Americanos/educação , Indígenas Norte-Americanos/etnologia , Indígenas Norte-Americanos/história , Meio-Oeste dos Estados Unidos/etnologia , Relações Raciais/história , Grupos Raciais/educação , Grupos Raciais/etnologia , Grupos Raciais/história , Varíola/etnologia , Varíola/história , Condições Sociais/históriaRESUMO
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm based on two-dimensional (2D) active shape models (ASM) for semi-automatic segmentation of the prostate boundary from ultrasound images. Optimisation of the 2D ASM for prostatic ultrasound was done first by examining ASM construction and image search parameters. Extension of the algorithm to three-dimensional (3D) segmentation was then done using rotational-based slicing. Evaluation of the 3D segmentation algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. Minimum description length landmark placement for ASM construction, and specific values for constraints and image search were found to be optimal. Evaluation of the algorithm versus gold standard boundaries found an average mean absolute distance of 1.09+/-0.49 mm, an average percent absolute volume difference of 3.28+/-3.16%, and a 5x speed increase versus manual segmentation.
Assuntos
Interpretação de Imagem Assistida por Computador , Imageamento Tridimensional , Modelos Biológicos , Próstata/diagnóstico por imagem , Algoritmos , Humanos , Masculino , Próstata/patologia , UltrassonografiaRESUMO
Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09+/-0.49 mm, the average percent absolute volume difference was 3.28+/-3.16%, and a 5x speed increase as compared manual planimetry was achieved.
