Retinal stroke prediction using logistic-based fusion of multiscale fractal analysis

Author

Azemin, M. Z Che ; Kumar, Dinesh K. ; Wong, T.Y. ; Wang, J.J. ; Kawasaki, R. ; Mitchell, P.

Author_Institution

Sch. of Electr. & Comput. Eng., RMIT Univ., Melbourne, VIC, Australia

fYear

2010

fDate

1-2 July 2010

Firstpage

125

Lastpage

128

Abstract

Medical images enhanced at different scales have shown to give good results in mammogram enhancement, tumor classification, and lung nodule detection. However, the studies of multiscale analysis on retinal vasculature have been primarily limited to vessel segmentation. We propose using the Fourier Fractal dimension (FFD) to extract the complexity of the retinal vasculature enhanced at different wavelet scales and a model was formulated for stroke prediction. Sensitivity and specificity were found to be 72.52% and 69.67% respectively.

Keywords

Fourier analysis; blood vessels; eye; fractals; image segmentation; medical image processing; Fourier Fractal dimension; logistic based fusion; lung nodule detection; m,ultiscale fractal analysis; mammogram enhancement; medical image; retinal stroke prediction; retinal vasculature; tumor classification; vessel segmentation; Biomedical computing; Biomedical imaging; Cameras; Fractals; Image analysis; Image segmentation; Lung neoplasms; Performance analysis; Predictive models; Retina; fractal; multiscale wavelet; retina;

fLanguage

English

Publisher

ieee

Conference_Titel

Imaging Systems and Techniques (IST), 2010 IEEE International Conference on

Conference_Location

Thessaloniki

Print_ISBN

978-1-4244-6492-0

Type

conf

DOI

10.1109/IST.2010.5548470

Filename

5548470