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A novel approach to diagnose diabetes based on the fractal characteristics of retinal images.
Cheng, Shu-Chen; Huang, Yueh-Min.
Afiliación
  • Cheng SC; Department of Engineering Science, National Cheng Hung University, Tainan 701, Taiwan, ROC. kittyc@gps.sv.ncku.edu.tw
IEEE Trans Inf Technol Biomed ; 7(3): 163-70, 2003 Sep.
Article en En | MEDLINE | ID: mdl-14518729
A novel diagnostic scheme to develop quantitative indexes of diabetes is introduced in this paper. The fractal dimension of the vascular distribution is estimated because we discovered that the fractal dimension of a severe diabetic patient's retinal vascular distribution appears greater than that of a normal human's. The issue of how to yield an accurate fractal dimension is to use high-quality images. To achieve a better image-processing result, an appropriate image-processing algorithm is adopted in this paper. Another important fractal feature introduced in this paper is the measure of lacunarity, which describes the characteristics of fractals that have the same fractal dimension but different appearances. For those vascular distributions in the same fractal dimension, further classification can be made using the degree of lacunarity. In addition to the image-processing technique, the resolution of original image is also discussed here. In this paper, the influence of the image resolution upon the fractal dimension is explored. We found that a low-resolution image cannot yield an accurate fractal dimension. Therefore, an approach for examining the lower bound of image resolution is also proposed in this paper. As for the classification of diagnosis results, four different approaches are compared to achieve higher accuracy. In this study, the fractal dimension and the measure of lacunarity have shown their significance in the classification of diabetes and are adequate for use as quantitative indexes.
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Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oftalmoscopía / Algoritmos / Interpretación de Imagen Asistida por Computador / Fractales / Diabetes Mellitus / Retinopatía Diabética Tipo de estudio: Diagnostic_studies / Etiology_studies / Evaluation_studies Límite: Humans Idioma: En Revista: IEEE Trans Inf Technol Biomed Asunto de la revista: INFORMATICA MEDICA Año: 2003 Tipo del documento: Article Pais de publicación: Estados Unidos
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Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Oftalmoscopía / Algoritmos / Interpretación de Imagen Asistida por Computador / Fractales / Diabetes Mellitus / Retinopatía Diabética Tipo de estudio: Diagnostic_studies / Etiology_studies / Evaluation_studies Límite: Humans Idioma: En Revista: IEEE Trans Inf Technol Biomed Asunto de la revista: INFORMATICA MEDICA Año: 2003 Tipo del documento: Article Pais de publicación: Estados Unidos