RESUMEN
A novel procedure using phase congruency is proposed for discriminating some lung disease using chest radiograph. Phase congruency provides information about transitions between adjacent pixels. Abrupt changes of phase congruency values between pixels may suggest a possible boundary or another feature that may be used for discrimination. This property of phase congruency may have potential for deciding between disease present and disease absent where the regions of infection on the images have no obvious shape, size, or configuration. Five texture measures calculated from phase congruency and Gabor were shown to be normally distributed. This gave good indicators of discrimination errors in the form of the probability of Type I Error (δ) and the probability of Type II Error (ß). However, since 1 - δ is the true positive fraction (TPF) and ß is the false positive fraction (FPF), an ROC analysis was used to decide on the choice of texture measures. Given that features are normally distributed, for the discrimination between disease present and disease absent, energy, contrast, and homogeneity from phase congruency gave better results compared to those using Gabor. Similarly, for the more difficult problem of discriminating lobar pneumonia and lung cancer, entropy and homogeneity from phase congruency gave better results relative to Gabor.
Asunto(s)
Enfermedades Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/diagnóstico por imagen , Neumonía/diagnóstico por imagen , Algoritmos , Humanos , Modelos Estadísticos , Probabilidad , Neumología/métodos , Curva ROC , Radiografía Torácica , Reproducibilidad de los ResultadosRESUMEN
This paper investigates a novel statistical discrimination procedure to detect PTB when the gold standard requirement is taken into consideration. Archived data were used to establish two groups of patients which are the control and test group. The control group was used to develop the statistical discrimination procedure using four vectors of wavelet coefficients as feature vectors for the detection of pulmonary tuberculosis (PTB), lung cancer (LC), and normal lung (NL). This discrimination procedure was investigated using the test group where the number of sputum positive and sputum negative cases that were correctly classified as PTB cases were noted. The proposed statistical discrimination method is able to detect PTB patients and LC with high true positive fraction. The method is also able to detect PTB patients that are sputum negative and therefore may be used as a complement to the gold standard.
Asunto(s)
Algoritmos , Interpretación Estadística de Datos , Interpretación de Imagen Radiográfica Asistida por Computador/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/normas , Radiografía Torácica/métodos , Radiografía Torácica/normas , Tuberculosis Pulmonar/diagnóstico por imagen , Humanos , Malasia , Guías de Práctica Clínica como Asunto , Reproducibilidad de los Resultados , Sensibilidad y EspecificidadRESUMEN
STATEMENT OF PROBLEM: In rehabilitating edentulous patients, selecting appropriately sized teeth in the absence of preextraction records is problematic. PURPOSE: The purpose of this study was to investigate the relationships between some facial dimensions and widths of the maxillary anterior teeth to potentially provide a guide for tooth selection. MATERIAL AND METHODS: Sixty full dentate Malaysian adults (18-36 years) representing 2 ethnic groups (Malay and Chinese), with well aligned maxillary anterior teeth and minimal attrition, participated in this study. Standardized digital images of the face, viewed frontally, were recorded. Using image analyzing software, the images were used to determine the interpupillary distance (IPD), inner canthal distance (ICD), and interalar width (IA). Widths of the 6 maxillary anterior teeth were measured directly from casts of the subjects using digital calipers. Regression analyses were conducted to measure the strength of the associations between the variables (alpha=.10). RESULTS: The means (standard deviations) of IPD, IA, and ICD of the subjects were 62.28 (2.47), 39.36 (3.12), and 34.36 (2.15) mm, respectively. The mesiodistal diameters of the maxillary central incisors, lateral incisors, and canines were 8.54 (0.50), 7.09 (0.48), and 7.94 (0.40) mm, respectively. The width of the central incisors was highly correlated to the IPD (r=0.99), while the widths of the lateral incisors and canines were highly correlated to a combination of IPD and IA (r=0.99 and 0.94, respectively). CONCLUSIONS: Using regression methods, the widths of the anterior teeth within the population tested may be predicted by a combination of the facial dimensions studied.
Asunto(s)
Diente Canino/anatomía & histología , Diseño de Dentadura , Cara/anatomía & histología , Incisivo/anatomía & histología , Diente Artificial , Adolescente , Adulto , Pueblo Asiatico , Cefalometría/métodos , China/etnología , Femenino , Humanos , Procesamiento de Imagen Asistido por Computador , Análisis de los Mínimos Cuadrados , Modelos Lineales , Malasia , Masculino , Maxilar , Odontometría/métodos , Fotograbar , Análisis de Regresión , Estadísticas no Paramétricas , Adulto JovenRESUMEN
This paper presents a statistical method for the detection of lobar pneumonia when using digitized chest X-ray films. Each region of interest was represented by a vector of wavelet texture measures which is then multiplied by the orthogonal matrix Q(2). The first two elements of the transformed vectors were shown to have a bivariate normal distribution. Misclassification probabilities were estimated using probability ellipsoids and discriminant functions. The result of this study recommends the detection of pneumonia by constructing probability ellipsoids or discriminant function using maximum energy and maximum column sum energy texture measures where misclassification probabilities were less than 0.15.